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Journal articles on the topic 'Information retrival'

Author: Grafiati
Published: 4 June 2021
Last updated: 20 February 2023

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1

Rudiansyah, Rudiansyah, Rafly Ariyansyah, Rian Nanda, and Ovi Wiranda. "Search Engine Menggunakan Metode Information Retrival." Jurnal SANTI - Sistem Informasi dan Teknik Informasi 2, no. 1 (June 15, 2022): 49–55. http://dx.doi.org/10.58794/santi.v2i1.68.

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Pencarian data pada database yang biasa dilakukan oleh kebanyakan orang hanya mampu mencari judul artikel yang sesuai berdasarkan kata kunci yang diinputkan, Contoh, jika kata kunci yang dimasukkan adalah “Kecerdasan buatan” maka akan yang ditampilkan semua dokumen yang mengandung kata “Kecerdasan buatan” namun sistem tidak bisa mengukur mana dokumen yang paling mirip. Oleh karna itu ,untuk dapat memenuhi kebutuhan pengguna dalam menemukan keyword yang cocok tetapi dapat mewakili data tersebut, kemudian sistem menghitung kemiripan antara keyword dengan daftar dokumen yang diwakili oleh kata perkata di dalam form. Artikel akan di tampilakn berdasarkan kata yang paling mirip. Dari hasil yang di dapat Ketika kita masukan keyword “android” maka akan tampil empat dokumen yang diurutkan sesuai tingkat kemiripannya, yaitu docId 3 dengan tingkat kemiripan 0.9512, docId 4 dengan tingkat kemiripan 0.5020, docId 2 dengan tingkat kemiripan 0.2671, docId 8 dengan tingkat kemiripan 0.1522.
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Setiawan, Gede Herdian, and I. Made Budi Adnyana. "Information Retrieval Pada Frequently Asked Questions (FAQ) dengan metode String Similarity." Techno.Com 21, no. 4 (November 30, 2022): 847–55. http://dx.doi.org/10.33633/tc.v21i4.6843.

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Information retrieval merupakan sebuah sarana untuk menemukan informasi berdasarkan kumpulan informasi pada data terstruktur maupun tidak terstruktur secara otomatis. implementasi information retrival seperti mesin pencari menggunakan query dari pengguna dengan bahasa alami manusia kemudian sistem dapat menemukan dokumen atau informasi yang berkaitan dengan query dari pengguna. Pada penelitian ini di usulkan sistem information retrieval pada Frequently Asked Questions atau FAQ dengan mencari pertanyaan yang mirip (similar) pada daftar pertanyaan di basis data terhadap pertanyaan yang diberikan oleh pengguna menggunakan algoritma Cosine similarity untuk mencari kesamaan kosinus tertinggi. Selanjutnya memberikan respon jawaban yang sebelum nya sudah di berikan label terhadap pertanyaan yang relevan dan memiliki similaritas paling tinggi. Telah dihasilkan dataset FAQ dan dilakukan preprocessing, penerapan algoritma Cosine Similarity terhadap input pertanyaan (query) dengan dataset dan menghasilkan bobot pada setiap pertanyaan (label) pada dataset. Melalui evaluasi akurasi pemberian bobot similaritas yang dilakukan dengan memberikan sembilan input pertanyaan dibagai pada tiga kategori berdasarkan tingkat kemiripan memiliki akurasi mencapai 100%, dengan demikian information retrieval dengan Cosine similarity telah mampu memberikan bobot sesuai dengan tingkat similaritas pertanyaan (query) dengan dataset pertanyaan pada FAQ
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3

Smith, Philip J., Deborah A. Krawczak, Steven J. Shute, and Mark Chignell. "Cognitive Engineering Issues in the Design of a Knowledge-Based Information Retrieval System." Proceedings of the Human Factors Society Annual Meeting 29, no. 4 (October 1985): 362–66. http://dx.doi.org/10.1177/154193128502900411.

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EP-X (Environmental Pollution expert) is a prototype expert system that acts as an expert search intermediary for a bibliographic information retrieval system. It searches for documents in the Chemical Abstracts database in the domain of environmental pollution, providing an intelligent human-computer interface that accommodates a wide variety of user backgrounds and interests. This paper discusses 1) the general problem of bibliographic information retrival, 2) the value of combining Artificial Intelligence (AI) and Human Factors Engineering (HFE) techniques in the design of an intelligent human-computer interface. 3) the general architecture and functioning of EP-X, and 4) examples of specific issues that arise when attempting to apply both AI and HFE techniques to the design of an interactive computer system.
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H. Al-Ibrahim, Ali Mohammad. "Fuzzy Logic System for Retrieval of Information in Electronic Libraries." Modern Applied Science 13, no. 11 (October 22, 2019): 76. http://dx.doi.org/10.5539/mas.v13n11p76.

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This research represents one of the steps aimed to address one of the most important challenges on the Web and digital libraries, which is compute  the rank of the document’s, and its importance, and their relevance to the user and to meet their needs for information, and so by taking advantage of the vast potential of logic Fuzzy in dealing with this kind of problems, and provide high flexibility for the user to clarify the issues and areas that interested them. This research is concernd on the design and implementation of a proposal for the information retrieval system, called Fuzzy Information Retrieval System(FZIRS). This system is designed to deal with a huge distributed database on a group of computers (servers) associated with the Intranet network specially designed to work the system, which includes different types and sizes of text files. The proposed system has the ability for mining of data mining from the database and retrieve useful information from them and that meet the user's needs well. This accomlished  through the applying of the proposed algorithms for indexing operations and calculate the rank of documents and generate keywords operations and display the  retrival results, which showed high quality when calculating results compared with other Information retrieving algorithms.
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Mubatada'i, Nur Rosyid, Ali Ridho Barakbah, and Afrida Helen. "Semantic Information Retrival for Scientific Experimental Papers with Knowlege based Feature Extraction." INOVTEK Polbeng - Seri Informatika 4, no. 1 (June 17, 2019): 76. http://dx.doi.org/10.35314/isi.v4i1.885.

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Tamrakar, Anjana. "Relevance Feedback For Information Retrival Based on User Query Using SIFT Algorithm." International Journal for Research in Applied Science and Engineering Technology 6, no. 6 (June 30, 2018): 1094–98. http://dx.doi.org/10.22214/ijraset.2018.6161.

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7

Ajay Kumar, A., Tenali Ravi Kumar, and T. Bala Akhil Reddy. "Human resource management leave and tour management data retrival system." International Journal of Engineering & Technology 7, no. 2.8 (March 19, 2018): 186. http://dx.doi.org/10.14419/ijet.v7i2.8.10403.

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This paper assembles a progressive learning-based research show organizing human resource organization system (HRMS) and legitimate execution from the perspective of various levelled learning structure is usefulto decreasethe costs also it saves the time, joining and altering Human Resource tries to whatever is left of the partnership. Experts will be locked in and secure with more information and decreaseover their work life. With this Human Resource Management Framework one can easily develop the work frameworks and approach. The fit flexibility features keep delegates present and fulfilling, even as statutes and controls change. For gifted relationship of commercial process, computerization in the current circumstance. The fundamental reason for the undertaking is to build up a HRM structure is the Intranet Automation of HR Software .HR framework gives the data with respect to the pros I the affiliation.
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Huang, Shuai, Jianli Ding, Jie Zou, Bohua Liu, Junyong Zhang, and Wenqian Chen. "Soil Moisture Retrival Based on Sentinel-1 Imagery under Sparse Vegetation Coverage." Sensors 19, no. 3 (January 30, 2019): 589. http://dx.doi.org/10.3390/s19030589.

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Soil moisture is an important aspect of heat transfer process and energy exchange between land-atmosphere systems, and it is a key link to the surface and groundwater circulation and land carbon cycles. In this study, according to the characteristics of the study area, an advanced integral equation model was used for numerical simulation analysis to establish a database of surface microwave scattering characteristics under sparse vegetation cover. Thus, a soil moisture retrieval model suitable for arid area was constructed. The results were as follows: (1) The response of the backscattering coefficient to soil moisture and associated surface roughness is significantly and logarithmically correlated under different incidence angles and polarization modes, and, a database of microwave scattering characteristics of arid soil surface under sparse vegetation cover was established. (2) According to the Sentinel-1 radar system parameters, a model for retrieving spatial distribution information of soil moisture was constructed; the soil moisture content information was extracted, and the results were consistent with the spatial distribution characteristics of soil moisture in the same period in the research area. (3) For the 0–10 cm surface soil moisture, the correlation coefficient between the simulated value and the measured value reached 0.8488, which means that the developed retrieval model has applicability to derive surface soil moisture in the oasis region of arid regions. This study can provide method for real-time and large-scale detection of soil moisture content in arid areas.
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Qodim, Husnul, Herningsih Herningsih, Phong Thanh Nguyen, Quyen Le Hoang Thuy To Nguyen, and Apriana Toding. "Educating the Information Integration Using Contextual Knowledge and Ontology Merging in Advanced Levels." International Journal of Higher Education 8, no. 8 (December 23, 2019): 24. http://dx.doi.org/10.5430/ijhe.v8n8p24.

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This paper defines the methods of educating the information integration by the use of ontologies. For this there are two various architecture are central and peer-to-peer data integration. A ciis generally has a worldwide mapping, which gives the client a uniform interface to get to data put away in the information sources. Conversely, in piis, there are no worldwide purposes of control on the information sources. Such systems enable developers to develop an integrated hybrid contextual based system and new concepts to be introduced. This enables the retrival of the information is easier and faster. The two most significant methodologies for structure an information integration framework is global as view & local as view (lav). In the gav method, each substance in the worldwide pattern is related nearby outline. In this paper we use various ontology languages like xml, rdf, daml+oil, owl etc.
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10

Kusuma, Dine Tiara. "Fast Fourier Transform (FFT) Dalam Transformasi Sinyal Frekuensi Suara Sebagai Upaya Perolehan Average Energy (AE) Musik." Petir 14, no. 1 (October 2, 2020): 28–35. http://dx.doi.org/10.33322/petir.v14i1.1022.

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Frekuensi Suara adalah getaran sinyal yang terdengar oleh manusia yang dihasilkan oleh gelombang bunyi yang memiliki frekuensi antara 20 Hz hingga 20.000 Hz. Dalam sistem temu kembali informasi dari sebuah musik diperlukan proses ektraksi musik menjadi sinyal frekuensi suara.Tujuan dari penelitian ini adalah untuk mencari nilai Average Energy (AE) yang merupakan salah satu parameter yang digunakan dalam information music retrival. Fast Fourier Transform (FFT) adalah metode yang digunakan untuk mentransformasi sinyal suara menjadi spectrum suara berbasis sinyal frekuensi yang dapat digunakan dalam proses analisa data suara lebih lanjut. Berdasarkan ujicoba dari musik yang digunakan pada penelitian ini diperoleh nilai Average Energy (AE) sebesar 0.00044998
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11

Aya Mamlu’ah. "METODE LOTRE PESANTREN TAHFIDZ AL-QUR’AN AT-TAUHID LERAN SENORI TUBAN ANALISIS TERHADAP PENCAPAIAN HAFALAN AL-QUR’AN DAN PERMASALAHANNYA." Visipena Journal 10, no. 1 (June 30, 2019): 148–63. http://dx.doi.org/10.46244/visipena.v10i1.497.

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Memorize the Qur'an was given power or memory included. Memory into memory in the framework of the structure of human life, that the process of memory in a psychological perspective covers three components, namely encoding, storage and retrival. The method or manner is crucial in achieving the success of memorizing the Qur'an, due to succeed whether a purpose is determined by a method which is an integral part in the learning system. To get good results and effective-efficient sustainable interfere the Qur'an falls in the community prepared by memorizing a truly embedded since someone menghatamkan to memorize Quran 30 Juz, because phenomenon that occurs when a interfere the Koran was not in the scope of the boarding school and is already busy with his life, memorizing the Qur'an ever memorized much less secure. Therefore the Pesantren Tahfidz Al-Quran At-Tawheed has implemented a new method of memorization by using a lottery method. This research method using qualitative research is descriptive qualitative approach, using the Phenomenology. It was found from the lottery method is a method which uses the random lottery (a kind of lottery arisan) written by juz juz-who has mastered memorizing of the students who have finished the memorized the Qur'an. So the interfere of the Koran must be completely memorized the outside heads when on the stage of this lottery or belongs on kompenan remember (memorize) or that can be called with retrival/processes calling back, the process of recalling information encoding results as well as storaging. The result of the application of the method of the lottery is to interfere in the Qur'an is stronger and be careful in keeping the memorizing them and interfere the Qur'an easier given Al-Quran memorizing them because during the process of this lottery method penghafal The Qur'an as a fervent and full concentration to undergo the process. Achievement of memorizing the Quran using the lottery this is students being challenged to memorize the Qur'an are seriously so that when on stage this method students could really mastered and memorized smoothly memorizing the Quran 30 juz even still remember though it's already in another flurry. The form of the problem is the students felt the lottery method is a scary thing because when these Lottery stage students need through previous methods i.e. unity method, sima'i method, method b, method and combined methods of jama '. Abstrak Menghafal Al-Qur’an adalah termasuk daya mengingat atau memory. Memori menjadi kerangka ingatan dalam struktur kehidupan manusia, bahwa proses memory dalam perspektif psikologis meliputi tiga komponen, yakni encoding, storage dan retrival. Metode atau cara sangat penting dalam mencapai keberhasilan menghafal Al-Qur’an, karena berhasil tidaknya suatu tujuan ditentukan oleh metode yang merupakan bagian integral dalam sistem pembelajaran. Untuk mendapatkan hasil yang baik dan efektif-efisien secara berkelanjutan para penghafal Al-Qur’an dipersiapkan terjun di masyarakat dengan hafalan yang benar-benar tertanam semenjak seseorang menghafalkan sampai menghatamkan Al-Qur’an 30 Juz, karena fenomena yang terjadi ketika seorang penghafal Al-Qur’an sudah tidak dalam ruang lingkup pesantren dan sudah sibuk dengan kehidupannya hafalan Al-Qur’an yang pernah dihafalkan banyak yang kurang terjaga. Oleh karenanya Pesantren Tahfidz Al-Qur’an At-Tauhid telah menerapkan metode menghafal baru dengan menggunakan metode lotre. Metode penelitian ini menggunakan penelitian kualitatif yang bersifat deskriptif, dengan menggunakan pendekatan kualitatif fenomenologi. Hal yang ditemukan dari metode lotre adalah sebuah metode acak yang menggunakan lotre (semacam lotre arisan) yang ditulis dengan juz-juz yang telah dikuasai dari hafalan para santri yang telah selesai menghafalkan Al-Qur’an. Jadi para penghafal Al-Qur’an harus benar-benar hafal diluar kepala ketika pada tahap lotre ini atau tergolong pada kompenan mengingat (menghafal) atau yang bisa disebut dengan retrival/proses memanggil kembali, proses recalling information hasil encoding maupun storaging. Hasil dari penerapan metode lotre tersebut adalah penghafal Al-Qur’an lebih kuat dan berhati-hati dalam menjaga hafalan mereka dan para penghafal Al-Qur’an lebih mudah mengingat hafalan Al-Qur’an mereka karena selama proses metode lotre ini penghafal Al-Qur’an secara sungguh-sungguh dan penuh konsentrasi untuk menjalani proses tersebut. Pencapaian hafalan Al-Qur’an dengan menggunakan metode lotre ini adalah santri menjadi tertantang untuk menghafalkan Al-Qur’an secara serius agar ketika pada tahap metode ini santri benar-benar bisa menguasai dan hafal dengan lancar hafalan Al-Qur’an 30 juz bahkan tetap ingat meskipun sudah dalam kesibukan lainnya. Bentuk permasalahannya adalah santri merasa metode lotre tersebut suatu hal yang menakutkan karena ketika tahap lotre ini santri perlu melalui metode-metode sebelumnya yakni metode wahdah, metode sima’i, metode kitabah, metode gabungan dan metode jama’. Kata Kunci: Al-Qur’an, Menghafal, Metode
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P, Jennifer. "Indexing Techniques on Information Retrieval." International Journal of Psychosocial Rehabilitation 24, no. 1 (January 20, 2020): 1716–20. http://dx.doi.org/10.37200/ijpr/v24i1/pr200271.

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13

Jalali, Ali, Shannon Hicks-Jalali, Robert J. Sica, Alexander Haefele, and Thomas von Clarmann. "A practical information-centered technique to remove a priori information from lidar optimal-estimation-method retrievals." Atmospheric Measurement Techniques 12, no. 7 (July 18, 2019): 3943–61. http://dx.doi.org/10.5194/amt-12-3943-2019.

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Abstract. Lidar retrievals of atmospheric temperature and water vapor mixing ratio profiles using the optimal estimation method (OEM) typically use a retrieval grid with a number of points larger than the number of pieces of independent information obtainable from the measurements. Consequently, retrieved geophysical quantities contain some information from their respective a priori values or profiles, which can affect the results in the higher altitudes of the temperature and water vapor profiles due to decreasing signal-to-noise ratios. The extent of this influence can be estimated using the retrieval's averaging kernels. The removal of formal a priori information from the retrieved profiles in the regions of prevailing a priori effects is desirable, particularly when these greatest heights are of interest for scientific studies. We demonstrate here that removal of a priori information from OEM retrievals is possible by repeating the retrieval on a coarser grid where the retrieval is stable even without the use of formal prior information. The averaging kernels of the fine-grid OEM retrieval are used to optimize the coarse retrieval grid. We demonstrate the adequacy of this method for the case of a large power-aperture Rayleigh scatter lidar nighttime temperature retrieval and for a Raman scatter lidar water vapor mixing ratio retrieval during both day and night.
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D, Lande, Soboliev A, and Dmytrenko O. "Intelligent technologies in information retrieval systems." Artificial Intelligence 27, jai2022.27(1) (June 20, 2022): 260–68. http://dx.doi.org/10.15407/jai2022.01.260.

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This paper considers the use of modern intelligent technologies in information retrieval systems. A general scheme for the implementation of Internet search engines is presented. The existing and prospective approaches to the intellectualization of individual components of this scheme are presented. An approach to the creation of a system of intelligent agents for information collection is presented. These agents are combined into teams and exchange the results of their work with each other. They form a reliable basis for the information base of search engines, ensure uninterrupted operation of the system in case of failure of individual agents. Methods for the formation of semantic networks corresponding to the texts of individual documents are also considered. These networks are considered as search patterns of documents for information retrieval and detection of duplicates or similar documents. Machine learning methods are used to conduct sentiment analysis. The paper describes an approach that made it possible to make the transition from the use of a naive Bayesian model to a modern machine learning system. The issues of cluster analysis and visualization of search results are also considered.
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S, Sangeetha, and Srividhya S.R. "Deconstructing Information Retrieval Systems with Plumbara." Journal of Advanced Research in Dynamical and Control Systems 11, no. 0009-SPECIAL ISSUE (September 25, 2019): 868–74. http://dx.doi.org/10.5373/jardcs/v11/20192645.

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Tang, Xiaoya. "Social Informatics and Information Retrieval Systems." Bulletin of the American Society for Information Science and Technology 26, no. 3 (January 31, 2005): 20–21. http://dx.doi.org/10.1002/bult.155.

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Routh, P. K., N. C. Sarkar, P. K. Das, D. Debnath, S. Bandyopadhyay, and U. Raj. "RETRIVAL OF BIO-PHYSICAL PARAMETERS IN SUNFLOWER CROP (<i>HELIANTHUS ANNUUS</i>) USING FIELD BASED HYPERSPECTRAL REMOTE SENSING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W6 (July 26, 2019): 623–29. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w6-623-2019.

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<p><strong>Abstract.</strong> Information on several crop bio-physical parameters is important as inputs for crop growth modelling, leaf stress analysis, crop health study and productivity point of view. Conventionally, biophysical parameters are measured in laboratory methods which are time consuming, laborious and destructive in nature. With the advent of remote sensing technology, the limitations of conventional methods can be overcome. Moreover, due to its narrow absorption bands at different wavelength, use of hyperspectral remote sensing becomes very useful in retrieving several bio-physical parameters. In the present study, field as well as laboratory based spectro-radiometer observations were carried out at Agronomy Department of VisvaBharati University, West Bengal, on Sunflower crop at its peak vegetation stage towards retrieving different bio-physical parameters, specifically leaf area index (LAI), chlorophyll content index (CCI), fluorescence etc. Different foliar boron (no boron, 0.15% and 0.20%) and irrigation (4&amp;ndash;6 irrigations) treatments, i.e. total nine treatments with three replications, were applied on sunflower crop during different phenological stages to achievemaximum ranges of the bio-physical parameters. The LAI, CCI and fluorescence parameters were collected using canopy analyzer,chlorophyll content meter and portable gas exchange system, respectively. In each of the treatments, total four hyperspectral measurements were collected, which were further corrected for noise and smoothened using Savitzky-Golay filtering. Total thirty-four narrow band indices were computed based on the hyperspectral data, and the regression analysis was carried out among the indices and bio-physical parameters. The regression parameters were further deployed on the hyperspectral indices to retrieve the bio-physical parameters. The Gitelson &amp; Merzylak-1 (GM-1) and Carter Indices-1 (CI-1) were found to the best indices for retrieving the LAI and CCI, respectively with correlation correlation (r) values of 0.87 and 0.80. On the other hand, Normalized Phaenophytinization Index (NPQI) and GM-1 were found to best for retrieving the Fv/Fm (dark) and Fvˈ/Fmˈ (light) with correlation(r)values of 0.92 and 0.76, respectively. Hence, the hyperspectral remote sensing be successfully utilized for retrieving several bio-physical parameters both at field (canopy level) and laboratory (leaf level) conditions.</p>
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Zhou, Minqiang, Bavo Langerock, Mahesh Kumar Sha, Nicolas Kumps, Christian Hermans, Christof Petri, Thorsten Warneke, et al. "Retrieval of atmospheric CH<sub>4</sub> vertical information from ground-based FTS near-infrared spectra." Atmospheric Measurement Techniques 12, no. 11 (November 25, 2019): 6125–41. http://dx.doi.org/10.5194/amt-12-6125-2019.

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Abstract. The Total Carbon Column Observing Network (TCCON) column-averaged dry air mole fraction of CH4 (XCH4) measurements have been widely used to validate satellite observations and to estimate model simulations. The GGG2014 code is the standard TCCON retrieval software used in performing a profile scaling retrieval. In order to obtain several vertical pieces of information in addition to the total column, in this study, the SFIT4 retrieval code is applied to retrieve the CH4 mole fraction vertical profile from the Fourier transform spectrometer (FTS) spectrum at six sites (Ny-Ålesund, Sodankylä, Bialystok, Bremen, Orléans and St Denis) during the time period of 2016–2017. The retrieval strategy of the CH4 profile retrieval from ground-based FTS near-infrared (NIR) spectra using the SFIT4 code (SFIT4NIR) is investigated. The degree of freedom for signal (DOFS) of the SFIT4NIR retrieval is about 2.4, with two distinct pieces of information in the troposphere and in the stratosphere. The averaging kernel and error budget of the SFIT4NIR retrieval are presented. The data accuracy and precision of the SFIT4NIR retrievals, including the total column and two partial columns (in the troposphere and stratosphere), are estimated by TCCON standard retrievals, ground-based in situ measurements, Atmospheric Chemistry Experiment – Fourier Transform Spectrometer (ACE-FTS) satellite observations, TCCON proxy data and AirCore and aircraft measurements. By comparison against TCCON standard retrievals, it is found that the retrieval uncertainty of SFIT4NIR XCH4 is similar to that of TCCON standard retrievals with systematic uncertainty within 0.35 % and random uncertainty of about 0.5 %. The tropospheric and stratospheric XCH4 from SFIT4NIR retrievals are assessed by comparison with AirCore and aircraft measurements, and there is a 1.0 ± 0.3 % overestimation in the SFIT4NIR tropospheric XCH4 and a 4.0 ± 2.0 % underestimation in the SFIT4NIR stratospheric XCH4, which are within the systematic uncertainties of SFIT4NIR-retrieved partial columns in the troposphere and stratosphere respectively.
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Kogan, S., N. Ash, R. A. Greenes, A. A. Boxwala, and Q. Zeng. "Characteristics of Consumer Terminology for Health Information Retrieval." Methods of Information in Medicine 41, no. 04 (2002): 289–98. http://dx.doi.org/10.1055/s-0038-1634490.

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Summary Objectives: As millions of consumers perform health information retrieval online, the mismatch between their terminology and the terminologies of the information sources could become a major barrier to successful retrievals. To address this problem, we studied the characteristics of consumer terminology for health information retrieval. Methods: Our study focused on consumer queries that were used on a consumer health service Web site and a consumer health information Web site. We analyzed data from the site-usage logs and conducted interviews with patients. Results: Our findings show that consumers’ information retrieval performance is very poor. There are significant mismatches at all levels (lexical, semantic and mental models) between the consumer terminology and both the information source terminology and standard medical vocabularies. Conclusions: Comprehensive terminology support on all levels is needed for consumer health information retrieval.
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P., Mahalakshmi. "An Art of Review on Conceptual based Information Retrieval." Webology 18, no. 1 (February 3, 2021): 51–61. http://dx.doi.org/10.14704/web/v18i1/web18026.

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21

J, Naren, Raja Rajeswari D, Nikhith Sannidhi, and Vithya G. "An Investigation on Ontology Based Fuzzy Semantic Information Retrieval." International Journal of Psychosocial Rehabilitation 23, no. 1 (February 20, 2019): 377–84. http://dx.doi.org/10.37200/ijpr/v23i1/pr190248.

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Guimarães, Thaís, and Rosa Inês de Novais Cordeiro. "O instagram e as hashtags como recurso para a recuperação da informação." Ámbitos. Revista Internacional de Comunicación, no. 53 (2021): 82–103. http://dx.doi.org/10.12795/ambitos.2021.i53.05.

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Pesquisa exploratória e descritiva que tem como objetivo examinar a natureza das hashtags como um recurso informacional para a nomeação e recuperação da informação do Instagram. O tagueamento é abordado como um processo que é realizado para a nomeação livre de fotos e vídeos pelos usuários mediante o uso de tags (etiquetas) na rede social estudada. O Instagram é compreendido como uma rede social de grande popularidade, que vem sendo cada vez mais aderido pela sociedade como fonte de informação, mas, por outro lado, aponta-se também a questão da desinformação. Apresenta as hashtags como uma forma de gestão de conteúdo, justificando seu uso como uma representação da informação que pode se beneficiar das técnicas de indexação. Utilizam-se como procedimentos metodológicos a pesquisa bibliográfica para levantamento da literatura referente ao tema em bases de dados e a pesquisa empírica que é realizada no ambiente do Instagram a fim da coleta da amostra e objeto de investigação. A abordagem adotada no estudo é quantiqualitativa, em que são examinadas as hashtags de fotos e vídeos empregadas em trinta e três perfis de viagens e turismo, resultando em 330 publicações, entre fotos e vídeos, e 945 hashtags diferentes. Estas são identificadas e examinadas conforme categorias de análise derivadas da literatura de Ciência da Informação. Os resultados são apresentados estatisticamente e comentados. Concluiu-se que as hashtags cumprem parcialmente a função de meio de busca de informação, mas a relação entre a fonte de informação (fotos e vídeos) e sua nomeação por meio de hashtags intuitivas apresentam problemas: entre outros, inconsistências em relação ao conteúdo. É preciso considerar a possibilidade da criação de orientações para o uso de hashtags no Instagram.
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Geddes, A., and H. Bösch. "Aerosol profile information from high resolution oxygen A-Band measurements from space." Atmospheric Measurement Techniques Discussions 7, no. 6 (June 17, 2014): 6021–63. http://dx.doi.org/10.5194/amtd-7-6021-2014.

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Abstract. Aerosols are an important factor of the Earth climatic system and they play a key role for air quality and public health. Observations of the oxygen A-Band at 760 nm can provide information on the vertical distribution of aerosols from passive satellite sensors, that can be of great interest for operational monitoring applications with high coverage if the aerosol information is obtained with sufficient precision, accuracy and vertical resolution. To address this issue, retrieval simulations of the aerosol vertical profile retrieval from O2 A Band observations by GOSAT, the upcoming OCO-2 and Sentinel 5-P mission and the proposed CarbonSat mission have been carried out. Precise retrievals of AOD within the boundary layer were found to favour low resolution, high SNR instruments such as Sentinel-5 P, whereas higher resolution instruments such as OCO-2 showed greater performance at higher altitudes and in information content above the boundary layer. Accurate retrievals of the AOD in the 0–2 km range appears difficult from all studied instruments and the retrieval errors typically exceed a value of 0.05. Constraining the surface albedo is a promising and effective way of improving the retrieval of aerosol, but the required level of a priori knowledge is very high. Due to the limited information content of the aerosol profile retrieval, the use of a parameterised aerosol distribution has been assessed and we show that the AOD and height of an aerosol layer can be retrieved well if the aerosol layer is uplifted to the free troposphere but errors are often large for aerosol layers in the boundary layer. Additional errors will be introduced by incorrect assumptions on surface pressure and aerosol type which can both bias retrieved AOD and height by up to 40%. We conclude the aerosol profile retrievals from O2 A Band using existing or upcoming satellite sensors will only provide limited information on aerosols in the boundary layer but such observations can be of great value for observing and mapping aerosol plumes in the free troposphere.
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Mielonen, T., J. F. de Haan, J. C. A. van Peet, M. Eremenko, and J. P. Veefkind. "Towards the retrieval of tropospheric ozone with the Ozone Monitoring Instrument (OMI)." Atmospheric Measurement Techniques 8, no. 2 (February 9, 2015): 671–87. http://dx.doi.org/10.5194/amt-8-671-2015.

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Abstract. We have assessed the sensitivity of the operational Ozone Monitoring Instrument (OMI) ozone profile retrieval algorithm to a number of a priori and radiative transfer assumptions. We studied the effect of stray light correction, surface albedo assumptions and a priori ozone profiles on the retrieved ozone profile. Then, we studied how to modify the algorithm to improve the retrieval of tropospheric ozone. We found that stray light corrections have a significant effect on the retrieved ozone profile but mainly at high altitudes. Surface albedo assumptions, on the other hand, have the largest impact at the lowest layers. Choice of an ozone profile climatology which is used as a priori information has small effects on the retrievals at all altitudes. However, the usage of climatological a priori covariance matrix has a significant effect. Based on these sensitivity tests, we made several modifications to the retrieval algorithm: the a priori ozone climatology was replaced with a new tropopause-dependent climatology, the a priori covariance matrix was calculated from the climatological ozone variability values, and the surface albedo was assumed to be linearly dependent on wavelength in the 311.5–330 nm channel. As expected, we found that the a priori covariance matrix basically defines the vertical distribution of degrees of freedom for a retrieval. Moreover, our case study over Europe showed that the modified version produced over 10% smaller ozone abundances in the troposphere which reduced the systematic overestimation of ozone in the retrieval algorithm and improved correspondence with Infrared Atmospheric Sounding Instrument (IASI) retrievals. The comparison with ozonesonde measurements over North America showed that the operational retrieval performed better in the upper troposphere/lower stratosphere (UTLS), whereas the modified version improved the retrievals in the lower troposphere and upper stratosphere. These comparisons showed that the systematic biases in the OMI ozone profile retrievals are not caused by the a priori information but by some still unidentified problem in the radiative transfer modelling. Instead, the a priori information pushes the systematically wrong ozone profiles towards the true values. The smaller weight of the a priori information in the modified retrieval leads to better visibility of tropospheric ozone structures, because it has a smaller tendency to damp the variability of the retrievals in the troposphere. In summary, the modified retrieval unmasks systematic problems in the radiative transfer/instrument model and is more sensitive to tropospheric ozone variation; that is, it is able to capture the tropospheric ozone morphology better.
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Jain, Sumit, and C. S. Bhatia C.S.Bhatia. "An Approach For Information Retrieval For Bookstores Using Formal Ontology." Indian Journal of Applied Research 1, no. 5 (October 1, 2011): 185–87. http://dx.doi.org/10.15373/2249555x/feb2012/69.

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26

K.N., Sridevi, and Prakasha S. "Doc-To-Tokens based Pre-Processing in Information Retrieval System." Webology 18, SI05 (October 30, 2021): 570–79. http://dx.doi.org/10.14704/web/v18si05/web18247.

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27

Amell, Adrià, Patrick Eriksson, and Simon Pfreundschuh. "Ice water path retrievals from Meteosat-9 using quantile regression neural networks." Atmospheric Measurement Techniques 15, no. 19 (October 12, 2022): 5701–17. http://dx.doi.org/10.5194/amt-15-5701-2022.

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Abstract. The relationship between geostationary radiances and ice water path (IWP) is complex, and traditional retrieval approaches are not optimal. This work applies machine learning to improve the IWP retrieval from Meteosat-9 observations, with a focus on low latitudes, training the models against retrievals based on CloudSat. Advantages of machine learning include avoiding explicit physical assumptions on the data, an efficient use of information from all channels, and easily leveraging spatial information. Thermal infrared (IR) retrievals are used as input to achieve a performance independent of the solar angle. They are compared with retrievals including solar reflectances as well as a subset of IR channels for compatibility with historical sensors. The retrievals are accomplished with quantile regression neural networks. This network type provides case-specific uncertainty estimates, compatible with non-Gaussian errors, and is flexible enough to be applied to different network architectures. Spatial information is incorporated into the network through a convolutional neural network (CNN) architecture. This choice outperforms architectures that only work pixelwise. In fact, the CNN shows a good retrieval performance by using only IR channels. This makes it possible to compute diurnal cycles, a problem that CloudSat cannot resolve due to its limited temporal and spatial sampling. These retrievals compare favourably with IWP retrievals in CLAAS, a dataset based on a traditional approach. These results highlight the possibilities to overcome limitations from physics-based approaches using machine learning while providing efficient, probabilistic IWP retrieval methods. Moreover, they suggest this first work can be extended to higher latitudes as well as that geostationary data can be considered as a complement to the upcoming Ice Cloud Imager mission, for example, to bridge the gap in temporal sampling with respect to space-based radars.
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Kwon, Eun-Han, B. J. Sohn, William L. Smith, and Jun Li. "Validating IASI Temperature and Moisture Sounding Retrievals over East Asia Using Radiosonde Observations." Journal of Atmospheric and Oceanic Technology 29, no. 9 (September 1, 2012): 1250–62. http://dx.doi.org/10.1175/jtech-d-11-00078.1.

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Abstract Temperature and moisture profiles retrieved from Infrared Atmospheric Sounding Interferometer (IASI) data are evaluated using collocated radiosonde data from September 2008 to August 2009 over East Asia. The level-2 products used in this study were provided by the National Oceanic and Atmospheric Administration/National Environmental Satellite, Data, and Information Service. By using radiosonde observations as a reference, the bias and root-mean-square error (RMSE) of the temperature and water vapor profiles are obtained to examine the performance of the IASI retrievals depending on surface types and the degree of atmospheric moisture. Overall, retrievals over the land or under drier atmospheric conditions show degraded performance for both the temperature and the moisture, especially for the boundary layer temperature. It is further shown that the vertical distributions of the RMSEs and the biases of the IASI retrievals resemble the variability pattern of the radiosonde observations from the mean profiles. These retrieval aspects are thought to be related to the surface emissivity effect on the IASI retrieval and the difficulties of accounting for large atmospheric variability in the retrieval process. Although the retrieval performance appears to degrade under cloudy conditions, cloudy- and clear-sky retrievals show similar statistical behaviors varying with surface type and atmospheric moisture. Furthermore, the similar statistical behaviors between first guess and final retrievals suggest that error characteristics inherent to the first guess were not sufficiently resolved by the physical retrieval process, leaving a need to improve the first guess for the better retrieval.
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29

Brenner, Everett H. "Information-Retrieval." Science & Technology Libraries 8, no. 1 (April 29, 1988): 61–73. http://dx.doi.org/10.1300/j122v08n01_06.

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BRAZIER, F. M. T., and J. J. BEISHUIZEN. "INFORMATION RETRIEVAL." ACM SIGCHI Bulletin 19, no. 4 (April 1988): 12–13. http://dx.doi.org/10.1145/43950.1047122.

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31

Editorial Submission, Haworth. "Information Retrieval." Collection Management 8, no. 3-4 (November 22, 1986): 231–34. http://dx.doi.org/10.1300/j105v08n03_63.

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32

S ,, Madhusudhan, Channakeshava K.R ,, and Dr T. Rangaswamy. "Content-Based Image Retrieval System for Optical Fiber Sensor Information Processing." International Journal of Engineering Research 3, no. 6 (June 1, 2014): 398–401. http://dx.doi.org/10.17950/ijer/v3s6/607.

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33

Hrabiec-Hojda, Patrycja, and Justyna Trzeciakowska. "Techniki wyszukiwania informacji w mediach społecznościowych dla celów białego wywiadu." Studia Politologiczne 2019, no. 54 (November 20, 2019): 175–90. http://dx.doi.org/10.33896/spolit.2019.54.7.

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Social media has become a popular information channel for a large part of society. The amount of information that is placed there every day remains mostly beyond the reach of search engines. The purpose of this article is to show the techniques and tools that can be used to search and explore social media. Only those tools that operate on the Polish market and are free at least in the basic version are presented.
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34

Kodabagi, M. M., Deepa Sarashetti, and Vilas Naik. "A Text Information Retrieval Technique for Big Data Using Map Reduce." Bonfring International Journal of Software Engineering and Soft Computing 6, Special Issue (October 31, 2016): 22–26. http://dx.doi.org/10.9756/bijsesc.8236.

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35

Zhu, Linyan, Ronglian Zhou, Di Di, Wenguang Bai, and Zijing Liu. "Retrieval of Atmospheric Water Vapor Content in the Environment from AHI/H8 Using Both Physical and Random Forest Methods—A Case Study for Typhoon Maria (201808)." Remote Sensing 15, no. 2 (January 13, 2023): 498. http://dx.doi.org/10.3390/rs15020498.

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The advanced imagers onboard the new generation of geostationary satellites could provide multilayer atmospheric moisture information with unprecedented high spatial and temporal resolutions, while the physical retrieval algorithm (One-Dimensional Variational, 1DVAR) is performed for operational atmospheric water vapor products with reduced resolutions, which is due to the limited computational efficiency of the physical retrieval algorithm. In this study, a typical cost-efficient machine learning (Random Forecast, RF) algorithm is adopted and compared with the physical retrieval algorithm for retrieving the atmospheric moisture from the measurements of Advance Himawari Imager (AHI) onboard the Himawari-8 satellite during the typhoon Maria (201808). It is found that the accuracy of the RF-based algorithm has much high computational efficiency and provides moisture retrievals with accuracy 35–45% better than that of 1DVAR, which means the retrieval process can be conducted at full spatial resolution for potential operational application. Both the Global Forecast System (GFS) forecasts and the AHI measurements are necessary information for moisture retrievals; they provide added value for each other.
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Levitan, Nathaniel, Barry Gross, Fred Moshary, and Yonghua Wu. "Potential Retrieval of Aerosol Microphysics From Multistatic Space-Borne Lidar." EPJ Web of Conferences 176 (2018): 05017. http://dx.doi.org/10.1051/epjconf/201817605017.

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HSRL lidars are being considered for deployment to space to retrieve aerosol microphysics. The literature is mostly focused on the monostatic configuration; but, in this paper, we explore whether additional information for the retrieval of microphysics can be obtained by adding a second detector in a bistatic configuration. The information gained from the additional measurements can under certain conditions reduce the ill-posed nature of aerosol microphysics retrieval and reducing the uncertainty in the retrievals.
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37

Geddes, A., and H. Bösch. "Tropospheric aerosol profile information from high-resolution oxygen A-band measurements from space." Atmospheric Measurement Techniques 8, no. 2 (February 20, 2015): 859–74. http://dx.doi.org/10.5194/amt-8-859-2015.

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Abstract. Aerosols are an important factor in the Earth climatic system and they play a key role in air quality and public health. Observations of the oxygen A-band at 760 nm can provide information on the vertical distribution of aerosols from passive satellite sensors that can be of great interest for operational monitoring applications with high spatial coverage if the aerosol information is obtained with sufficient precision, accuracy and vertical resolution. To address this issue, retrieval simulations of the aerosol vertical profile retrieval from O2 A-band observations by GOSAT, the upcoming Orbiting Carbon Observatory-2 (OCO-2) and Sentinel 5-P missions, and the proposed CarbonSat mission have been carried out. Precise retrievals of aerosol optical depth (AOD) within the boundary layer were found to favour low-resolution, high signal-to-noise instruments such as Sentinel-5 P, whereas higher-resolution instruments such as OCO-2 showed greater performance at higher altitudes and in information content above the boundary layer. Retrieval of the AOD in the 0–2 km range with precision appears difficult from all studied instruments and the retrieval errors typically exceed a value of 0.05 for AODs up to 0.3. Constraining the surface albedo is a promising and effective way of improving the retrieval of aerosol, but the accuracy of the required prior knowledge is very high. Due to the limited information content of the aerosol profile retrieval, the use of a parameterised aerosol distribution is assessed, and we show that the AOD and height of an aerosol layer can be retrieved well if the aerosol layer is uplifted to the free troposphere; however, errors are often large for aerosol layers in the boundary layer. Additional errors are introduced by incorrect assumptions on surface pressure and aerosol mixture, which can both bias retrieved AOD and height by up to 45%. In addition, assumptions of the boundary layer temperature are found to yield an additional error of up to 8%. We conclude that the aerosol profile retrievals from O2 A-band using existing or upcoming satellite sensors will only provide limited information on aerosols in the boundary layer but such observations can be of great value for observing and mapping aerosol plumes in the free troposphere.
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38

Mizzi, Arthur P., Avelino F. Arellano Jr., David P. Edwards, Jeffrey L. Anderson, and Gabriele G. Pfister. "Assimilating compact phase space retrievals of atmospheric composition with WRF-Chem/DART: a regional chemical transport/ensemble Kalman filter data assimilation system." Geoscientific Model Development 9, no. 3 (March 4, 2016): 965–78. http://dx.doi.org/10.5194/gmd-9-965-2016.

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Abstract. This paper introduces the Weather Research and Forecasting Model with chemistry/Data Assimilation Research Testbed (WRF-Chem/DART) chemical transport forecasting/data assimilation system together with the assimilation of compact phase space retrievals of satellite-derived atmospheric composition products. WRF-Chem is a state-of-the-art chemical transport model. DART is a flexible software environment for researching ensemble data assimilation with different assimilation and forecast model options. DART's primary assimilation tool is the ensemble adjustment Kalman filter. WRF-Chem/DART is applied to the assimilation of Terra/Measurement of Pollution in the Troposphere (MOPITT) carbon monoxide (CO) trace gas retrieval profiles. Those CO observations are first assimilated as quasi-optimal retrievals (QORs). Our results show that assimilation of the CO retrievals (i) reduced WRF-Chem's CO bias in retrieval and state space, and (ii) improved the CO forecast skill by reducing the Root Mean Square Error (RMSE) and increasing the Coefficient of Determination (R2). Those CO forecast improvements were significant at the 95 % level. Trace gas retrieval data sets contain (i) large amounts of data with limited information content per observation, (ii) error covariance cross-correlations, and (iii) contributions from the retrieval prior profile that should be removed before assimilation. Those characteristics present challenges to the assimilation of retrievals. This paper addresses those challenges by introducing the assimilation of compact phase space retrievals (CPSRs). CPSRs are obtained by preprocessing retrieval data sets with an algorithm that (i) compresses the retrieval data, (ii) diagonalizes the error covariance, and (iii) removes the retrieval prior profile contribution. Most modern ensemble assimilation algorithms can efficiently assimilate CPSRs. Our results show that assimilation of MOPITT CO CPSRs reduced the number of observations (and assimilation computation costs) by ∼ 35 %, while providing CO forecast improvements comparable to or better than with the assimilation of MOPITT CO QORs.
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39

Mizzi, A. P., A. F. Arellano, D. P. Edwards, J. L. Anderson, and G. G. Pfister. "Assimilating compact phase space retrievals of atmospheric composition with WRF-Chem/DART: a regional chemical transport/ensemble Kalman filter data assimilation system." Geoscientific Model Development Discussions 8, no. 9 (September 8, 2015): 7693–725. http://dx.doi.org/10.5194/gmdd-8-7693-2015.

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Abstract. This paper introduces the Weather Research and Forecasting Model with chemistry/Data Assimilation Research Testbed (WRF-Chem/DART) chemical transport forecasting/data assimilation system together with the assimilation of "compact phase space retrievals" of satellite-derived atmospheric composition products. WRF-Chem is a state-of-the-art chemical transport model. DART is a flexible software environment for researching ensemble data assimilation with different assimilation and forecast model options. DART's primary assimilation tool is the ensemble adjustment Kalman filter. WRF-Chem/DART is applied to the assimilation of Terra/Measurement of Pollution in the Troposphere (MOPITT) carbon monoxide (CO) trace gas retrieval profiles. Those CO observations are first assimilated as quasi-optimal retrievals (QORs). Our results show that assimilation of the CO retrievals: (i) reduced WRF-Chem's CO bias in retrieval and state space, and (ii) improved the CO forecast skill by reducing the Root Mean Square Error (RMSE) and increasing the Coefficient of Determination (R2). Those CO forecast improvements were significant at the 95 % level. Trace gas retrieval data sets contain: (i) large amounts of data with limited information content per observation, (ii) error covariance cross-correlations, and (iii) contributions from the retrieval prior profile that should be removed before assimilation. Those characteristics present challenges to the assimilation of retrievals. This paper addresses those challenges by introducing the assimilation of "compact phase space retrievals" (CPSRs). CPSRs are obtained by preprocessing retrieval datasets with an algorithm that: (i) compresses the retrieval data, (ii) diagonalizes the error covariance, and (iii) removes the retrieval prior profile contribution. Most modern ensemble assimilation algorithms can efficiently assimilate CPSRs. Our results show that assimilation of MOPITT CO CPSRs reduced the number of observations (and assimilation computation costs) by ~ 35 % while providing CO forecast improvements comparable to or better than with the assimilation of MOPITT CO QORs.
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40

Wu, Lianghai, Otto Hasekamp, Haili Hu, Joost aan de Brugh, Jochen Landgraf, Andre Butz, and Ilse Aben. "Full-physics carbon dioxide retrievals from the Orbiting Carbon Observatory-2 (OCO-2) satellite by only using the 2.06 µm band." Atmospheric Measurement Techniques 12, no. 11 (November 21, 2019): 6049–58. http://dx.doi.org/10.5194/amt-12-6049-2019.

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Abstract. Passive remote sensing of atmospheric carbon dioxide uses spectroscopic measurements of sunlight backscattered by the Earth's surface and atmosphere. The current state-of-the-art retrieval methods use three different spectral bands, the oxygen A band at 0.76 µm and the weak and strong CO2 absorption bands at 1.61 and 2.06 µm, respectively, to infer information on light scattering and the carbon dioxide column-averaged dry-air mole fraction XCO2. In this study, we propose a one-band XCO2 retrieval technique which uses only the 2.06 µm band measurements from the Orbiting Carbon Observatory-2 (OCO-2) satellite. We examine the data quality by comparing the OCO-2 XCO2 with collocated ground-based measurements from the Total Carbon Column Observing Network (TCCON). Over land and ocean the OCO-2 one-band retrieval shows differences from TCCON observations with a standard deviation of ∼1.30 ppm and a station-to-station variability of ∼0.50 ppm. Moreover, we compare one-band and three-band retrievals over Europe, the Middle East, and Africa and see high correlation between the two retrievals with a SD of 0.93 ppm. Compared to the three-band retrievals, XCO2 retrievals using only the 2.06 µm band have similar retrieval accuracy, precision, and data yield.
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41

Fournier, N., P. Stammes, M. de Graaf, R. van der A, A. Piters, M. Grzegorski, and A. Kokhanovsky. "Improving cloud information over deserts from SCIAMACHY Oxygen A-band measurements." Atmospheric Chemistry and Physics 6, no. 1 (January 25, 2006): 163–72. http://dx.doi.org/10.5194/acp-6-163-2006.

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Abstract. The retrieval of column densities and concentration profiles of atmospheric trace gas species from satellites is sensitive to light scattered by clouds. The SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument on the Envisat satellite, principally designed to retrieve trace gases in the atmosphere, is also capable of detecting clouds. FRESCO (Fast Retrieval Scheme for Clouds from the Oxygen A-band) is a fast and robust algorithm providing cloud information from the O2 A-band for cloud correction of ozone. FRESCO provides a consistent set of cloud products by retrieving simultaneously effective cloud fraction and cloud top pressure. The FRESCO retrieved values are compared with the SCIAMACHY Level 2 operational cloud fraction of OCRA (Optical Cloud Recognition Algorithm) but, also, with cloud information from HICRU (Heidelberg Iterative Cloud Retrieval Utilities), SACURA (SemiAnalytical CloUd Retrieval Algorithm) and the MODIS (Moderate Resolution Imaging Spectroradiometer) instrument. The results correlate well, but FRESCO overestimates cloud fraction over deserts. Thus, to improve retrievals at these locations, the FRESCO surface albedo databases are decontaminated from the presence of desert dust aerosols. This is achieved by using the GOME Absorbing Aerosol Index. It is shown that this approach succeeds well in producing more accurate cloud information over the Sahara.
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42

Praus, Petr, and Pavel Praks. "Information retrieval in hydrochemical data using the latent semantic indexing approach." Journal of Hydroinformatics 9, no. 2 (March 1, 2007): 135–43. http://dx.doi.org/10.2166/hydro.2007.003b.

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The latent semantic indexing (LSI) method was applied for the retrieval of similar samples (those samples with a similar composition) in a dataset of groundwater samples. The LSI procedure was based on two steps: (i) reduction of the data dimensionality by principal component analysis (PCA) and (ii) calculation of a similarity between selected samples (queries) and other samples. The similarity measures were expressed as the cosine similarity, the Euclidean and Manhattan distances. Five queries were chosen so as to represent different sampling localities. The original data space of 14 variables measured in 95 samples of groundwater was reduced to the three-dimensional space of the three largest principal components which explained nearly 80% of the total variance. The five most proximity samples to each query were evaluated. The LSI outputs were compared with the retrievals in the orthogonal system of all variables transformed by PCA and in the system of standardized original variables. Most of these retrievals did not agree with the LSI ones, most likely because both systems contained the interfering data noise which was not preliminary removed by the dimensionality reduction. Therefore the LSI approach based on the noise filtration was considered to be a promising strategy for information retrieval in real hydrochemical data.
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43

Magdalenic, Ivan, Danijel Radosevic, and Zoran Skocir. "Dynamic Generation of Web Services for Data Retrieval Using Ontology." Informatica 20, no. 3 (January 1, 2009): 397–416. http://dx.doi.org/10.15388/informatica.2009.257.

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44

Shi, Chong, Makiko Hashimoto, and Teruyuki Nakajima. "Remote sensing of aerosol properties from multi-wavelength and multi-pixel information over the ocean." Atmospheric Chemistry and Physics 19, no. 4 (February 26, 2019): 2461–75. http://dx.doi.org/10.5194/acp-19-2461-2019.

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Abstract. In this study, we investigate the feasibility of a multi-pixel scheme in the inversion of aerosol optical properties for multispectral satellite instruments over the ocean. Different from the traditional satellite aerosol retrievals conducted pixel by pixel, we derive the aerosol optical thickness (AOT) of multiple pixels simultaneously by adding a smoothness constraint on the spatial variation of aerosols and oceanic substances, which helps the satellite retrieval, with higher consistency from pixel to pixel. Simulations are performed for two representative oceanic circumstances, open and coastal waters, as well as the land–ocean interface region. We retrieve the AOT for fine, sea spray, and dust aerosols simultaneously using synthetic spectral measurements, which are from the Greenhouse Gases Observing Satellite and Thermal and Near Infrared Sensor for Carbon Observation – Cloud and Aerosol Imager (GOSAT∕TANSO-CAI), with four wavelengths ranging from the ultraviolet to shortwave infrared bands. The forward radiation calculation is performed by a coupled atmosphere–ocean radiative transfer model combined with a three-component bio-optical oceanic module, where the chlorophyll a concentration, sediment, and colored dissolved organic matter are considered. Results show that accuracies of the derived AOT and spectral remote-sensing reflectance are both improved by applying smoothness constraints on the spatial variation of aerosol and oceanic substances in homogeneous or inhomogeneous surface conditions. The multi-pixel scheme can be effective in compensating for the retrieval biases induced by measurement errors and improving the retrieval sensitivity, particularly for the fine aerosols over the coastal water. We then apply the algorithm to derive AOTs using real satellite measurements. Results indicate that the multi-pixel method helps to polish the irregular retrieved results of the satellite imagery and is potentially promising for the aerosol retrieval over highly turbid waters by benefiting from the coincident retrieval of neighboring pixels. A comparison of retrieved AOTs from satellite measurements with those from the Aerosol Robotic Network (AERONET) also indicates that retrievals conducted by the multi-pixel scheme are more consistent with the AERONET observations.
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B, Gomathi. "Semantic Web Application in E-learning Using Protege based on Information Retrieval." Journal of Advanced Research in Dynamical and Control Systems 12, SP7 (July 25, 2020): 1847–55. http://dx.doi.org/10.5373/jardcs/v12sp7/20202297.

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46

R, Aravazhi, and Chidambaram M. "An Enhanced Semantic Similarity based Information Retrieval System in Mesh and EMR." Journal of Advanced Research in Dynamical and Control Systems 11, no. 0009-SPECIAL ISSUE (September 25, 2019): 993–98. http://dx.doi.org/10.5373/jardcs/v11/20192662.

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47

Wood, Norman B., and Tristan S. L'Ecuyer. "What millimeter-wavelength radar reflectivity reveals about snowfall: an information-centric analysis." Atmospheric Measurement Techniques 14, no. 2 (February 4, 2021): 869–88. http://dx.doi.org/10.5194/amt-14-869-2021.

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Abstract. The ability of single-frequency, millimeter-wavelength radar reflectivity observations to provide useful constraints for retrieval of snow particle size distribution (PSD) parameters, snowfall rates, and snowfall accumulations is examined. An optimal estimation snowfall retrieval that allows analyses of retrieval uncertainties and information content is applied to observations of near-surface W-band reflectivities from multiple snowfall events during the 2006–2007 winter season in southern Ontario. Retrieved instantaneous snowfall rates generally have uncertainties greater than 100 %, but single-event and seasonal snow accumulations from the retrieval results match well with collocated measurements of accumulations. Absolute fractional differences are mainly below 30 % for individual events that have more substantial accumulations and, for the season, 12.6 %. Uncertainties in retrieved snowfall rates are driven mainly by uncertainties in the retrieved PSD parameters, followed by uncertainties in particle model parameters and, to a lesser extent, the uncertainties in the fall-speed model. Uncertainties attributable to assuming an exponential distribution are negligible. The results indicate that improvements to PSD and particle model a priori constraints provide the most impactful path forward for reducing uncertainties in retrieved snowfall rates. Information content analyses reveal that PSD slope is well-constrained by the retrieval. Given the sensitivity of PSD slope to microphysical transformations, the results show that such retrievals, when applied to radar reflectivity profiles, could provide information about microphysical transformations in the snowing column. The PSD intercept is less well-constrained by the retrieval. While applied to near-surface radar observations in this study, the retrieval is applicable as well to radar observations aloft, such as those provided by profiling ground-based, airborne, and satellite-borne radars under lighter snowfall conditions when attenuation and multiple scattering can be neglected.
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48

Belkin, Nicholas J., and W. Bruce Croft. "Information filtering and information retrieval." Communications of the ACM 35, no. 12 (December 1992): 29–38. http://dx.doi.org/10.1145/138859.138861.

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49

van Rijsbergen, C. J., and M. Lalmas. "Information calculus for information retrieval." Journal of the American Society for Information Science 47, no. 5 (May 1996): 385–98. http://dx.doi.org/10.1002/(sici)1097-4571(199605)47:5<385::aid-asi6>3.0.co;2-s.

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50

Pfreundschuh, Simon, Ingrid Ingemarsson, Patrick Eriksson, Daniel A. Vila, and Alan J. P. Calheiros. "An improved near-real-time precipitation retrieval for Brazil." Atmospheric Measurement Techniques 15, no. 23 (December 1, 2022): 6907–33. http://dx.doi.org/10.5194/amt-15-6907-2022.

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Abstract. Observations from geostationary satellites can provide spatially continuous coverage at continental scales with high spatial and temporal resolution. Because of this, they are commonly used to complement ground-based precipitation measurements, whose coverage is often more limited. We present Hydronn, a neural-network-based, near-real-time precipitation retrieval for Brazil based on visible and infrared (Vis–IR) observations from the Advanced Baseline Imager (ABI) on the Geostationary Operational Environmental Satellite 16 (GOES-16). The retrieval, which employs a convolutional neural network to perform Bayesian precipitation retrievals, was developed with the aims of (1) leveraging the full potential of latest-generation geostationary observations and (2) providing probabilistic precipitation estimates with well-calibrated uncertainties. The retrieval is trained using more than 3 years of collocations with combined radar and radiometer retrievals from the Global Precipitation Measurement (GPM) core observatory over South America. The accuracy of instantaneous precipitation estimates is assessed using a separate year of GPM combined retrievals and compared to retrievals from passive microwave (PMW) sensors and HYDRO, the Vis–IR retrieval that is currently in operational use at the Brazilian Institute for Space Research. Using all available channels of the ABI, Hydronn achieves accuracy close to that of state-of-the-art PMW precipitation retrievals in both precipitation estimation and detection despite the lower information content of the Vis–IR observations. Hourly, daily, and monthly precipitation accumulations are evaluated against gauge measurements for June and December 2020 and compared to HYDRO, the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) Cloud Classification System (CCS), and the Integrated Multi-satellitE Retrievals for GPM (IMERG). Compared to HYDRO, Hydronn reduces the mean absolute error for hourly accumulations by 21 % (22 %) compared to HYDRO by 44 % (41 %) for the mean squared error (MSE) and increases the correlation by 138 % (312 %) for June (December) 2020. Compared to IMERG, the improvements correspond to 16 % (14 %), 12 % (12 %), and 20 % (56 %), respectively. Furthermore, we show that the probabilistic retrieval is well calibrated against gauge measurements when differences in the distributions of the training data and the gauge measurements are accounted for. Hydronn has the potential to significantly improve near-real-time precipitation retrievals over Brazil. Furthermore, our results show that precipitation retrievals based on convolutional neural networks (CNNs) that leverage the full range of available observations from latest-generation geostationary satellites can provide instantaneous precipitation estimates with accuracy close to that of state-of-the-art PMW retrievals. The high temporal resolution of the geostationary observation allows Hydronn to provide more accurate precipitation accumulations than any of the tested conventional precipitation retrievals. Hydronn thus clearly shows the potential of deep-learning-based precipitation retrievals to improve precipitation estimates from currently available satellite imagery.
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