Relevant bibliographies by topics / Information retrival

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Information retrival'

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

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Journal articles on the topic "Information retrival"

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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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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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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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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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Dissertations / Theses on the topic "Information retrival"

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Chen, Fanglan, and Taissia Goriounova. "Lexikonbaserad Cross-Language Information Retrival : Utvärdering av queryeffektivitet." Thesis, Högskolan i Borås, Institutionen Biblioteks- och informationsvetenskap / Bibliotekshögskolan, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-17983.

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This thesis discusses main problems associated with dictionary-based Cross-Language Information Retrieval as lexical and translational ambiguity of query terms, translation of compounds and phrases, dictionary limitation. The purpose of the study is to investigate how query structure influences the effectiveness of CLIR regarding performance of three query types: original query, unstructured query and structured query. Query structuring refers to the application of #syn-operator to group query terms. The study comprises an experiment that was performed in the InQuery IR system with TrecUta database that contains 550,000 news articles from different American newspapers. 24 topics were used for the experiment. The effectiveness of three types of query structure is compared at different Document Cut-off Value levels, maximal DCV= 100. The measure used is average precision. Binary relevance situation, where the three relevance degrees 1, 2, and 3 have been merged into one, is applied. The results show that dictionary-based query translation without the use of structure significantly decreases the effectiveness of information retrieval while query structuring through synonym sets shows to be a simple and effective method, which allows the reduction of the effects of translation ambiguity and the improvement of the performance of CLIR-queries. The results reveal that the performance can nearly reach the same level as the original queries.
Uppsatsnivå: D
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Li, Yuefeng, and mikewood@deakin edu au. "Modelling intelligent agents for web-based information gathering." Deakin University. School of Computing and Mathematics, 2000. http://tux.lib.deakin.edu.au./adt-VDU/public/adt-VDU20051201.151125.

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The recent emergence of intelligent agent technology and advances in information gathering have been the important steps forward in efficiently managing and using the vast amount of information now available on the Web to make informed decisions. There are, however, still many problems that need to be overcome in the information gathering research arena to enable the delivery of relevant information required by end users. Good decisions cannot be made without sufficient, timely, and correct information. Traditionally it is said that knowledge is power, however, nowadays sufficient, timely, and correct information is power. So gathering relevant information to meet user information needs is the crucial step for making good decisions. The ideal goal of information gathering is to obtain only the information that users need (no more and no less). However, the volume of information available, diversity formats of information, uncertainties of information, and distributed locations of information (e.g. World Wide Web) hinder the process of gathering the right information to meet the user needs. Specifically, two fundamental issues in regard to efficiency of information gathering are mismatch and overload. The mismatch means some information that meets user needs has not been gathered (or missed out), whereas, the overload means some gathered information is not what users need. Traditional information retrieval has been developed well in the past twenty years. The introduction of the Web has changed people's perceptions of information retrieval. Usually, the task of information retrieval is considered to have the function of leading the user to those documents that are relevant to his/her information needs. The similar function in information retrieval is to filter out the irrelevant documents (or called information filtering). Research into traditional information retrieval has provided many retrieval models and techniques to represent documents and queries. Nowadays, information is becoming highly distributed, and increasingly difficult to gather. On the other hand, people have found a lot of uncertainties that are contained in the user information needs. These motivate the need for research in agent-based information gathering. Agent-based information systems arise at this moment. In these kinds of systems, intelligent agents will get commitments from their users and act on the users behalf to gather the required information. They can easily retrieve the relevant information from highly distributed uncertain environments because of their merits of intelligent, autonomy and distribution. The current research for agent-based information gathering systems is divided into single agent gathering systems, and multi-agent gathering systems. In both research areas, there are still open problems to be solved so that agent-based information gathering systems can retrieve the uncertain information more effectively from the highly distributed environments. The aim of this thesis is to research the theoretical framework for intelligent agents to gather information from the Web. This research integrates the areas of information retrieval and intelligent agents. The specific research areas in this thesis are the development of an information filtering model for single agent systems, and the development of a dynamic belief model for information fusion for multi-agent systems. The research results are also supported by the construction of real information gathering agents (e.g., Job Agent) for the Internet to help users to gather useful information stored in Web sites. In such a framework, information gathering agents have abilities to describe (or learn) the user information needs, and act like users to retrieve, filter, and/or fuse the information. A rough set based information filtering model is developed to address the problem of overload. The new approach allows users to describe their information needs on user concept spaces rather than on document spaces, and it views a user information need as a rough set over the document space. The rough set decision theory is used to classify new documents into three regions: positive region, boundary region, and negative region. Two experiments are presented to verify this model, and it shows that the rough set based model provides an efficient approach to the overload problem. In this research, a dynamic belief model for information fusion in multi-agent environments is also developed. This model has a polynomial time complexity, and it has been proven that the fusion results are belief (mass) functions. By using this model, a collection fusion algorithm for information gathering agents is presented. The difficult problem for this research is the case where collections may be used by more than one agent. This algorithm, however, uses the technique of cooperation between agents, and provides a solution for this difficult problem in distributed information retrieval systems. This thesis presents the solutions to the theoretical problems in agent-based information gathering systems, including information filtering models, agent belief modeling, and collection fusions. It also presents solutions to some of the technical problems in agent-based information systems, such as document classification, the architecture for agent-based information gathering systems, and the decision in multiple agent environments. Such kinds of information gathering agents will gather relevant information from highly distributed uncertain environments.
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Schlaefer, Nico. "Statistical Source Expansion for Question Answering." Research Showcase @ CMU, 2011. http://repository.cmu.edu/dissertations/341.

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A source expansion algorithm automatically extends a given text corpus with related information from large, unstructured sources. While the expanded corpus is not intended for human consumption, it can be leveraged in question answering (QA) and other information retrieval or extraction tasks to find more relevant knowledge and to gather additional evidence for evaluating hypotheses. In this thesis, we propose a novel algorithm that expands a collection of seed documents by (1) retrieving related content from the Web or other large external sources, (2) extracting self-contained text nuggets from the related content, (3) estimating the relevance of the text nuggets with regard to the topics of the seed documents using a statistical model, and (4) compiling new pseudo-documents from nuggets that are relevant and complement existing information. In an intrinsic evaluation on a dataset comprising 1,500 hand-labeled web pages, the most elective statistical relevance model ranked text nuggets by relevance with 81% MAP, compared to 43% when relying on rankings generated by a web search engine, and 75% when using a multi-document summarization algorithm. These differences are statistically significant and result in noticeable gains in search performance in a task-based evaluation on QA datasets. The statistical models use a comprehensive set of features to predict the topicality and quality of text nuggets based on topic models built from seed content, search engine rankings and surface characteristics of the retrieved text. Linear models that evaluate text nuggets individually are compared to a sequential model that estimates their relevance given the surrounding nuggets. The sequential model leverages features derived from text segmentation algorithms to dynamically predict transitions between relevant and irrelevant passages. It slightly outperforms the best linear model while using fewer parameters and requiring less training time. In addition, we demonstrate that active learning reduces the amount of labeled data required to fit a relevance model by two orders of magnitude with little loss in ranking performance. This facilitates the adaptation of the source expansion algorithm to new knowledge domains and applications. Applied to the QA task, the proposed method yields consistent and statistically significant performance gains across different datasets, seed corpora and retrieval strategies. We evaluated the impact of source expansion on search performance and end-to-end accuracy using Watson and the OpenEphyra QA system, and datasets comprising over 6,500 questions from the Jeopardy! quiz show and TREC evaluations. By expanding various seed corpora with web search results, we were able to improve the QA accuracy of Watson from 66% to 71% on regular Jeopardy! questions, from 45% to 51% on Final Jeopardy! questions and from 59% to 64% on TREC factoid questions. We also show that the source expansion approach can be adapted to extract relevant content from locally stored sources without requiring a search engine, and that this method yields similar performance gains. When combined with the approach that uses web search results, Watson's accuracy further increases to 72% on regular Jeopardy! data, 54% on Final Jeopardy! and 67% on TREC questions.
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Silva, Rafael Hansen da. "Uma abordagem escalável para controle de acesso muitos para muitos em redes centradas de informação." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2016. http://hdl.handle.net/10183/140450.

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Um dos principais desafios em Redes Centradas em Informação (ICN) é como prover controle de acesso à publicação e recuperação de conteúdos. Apesar das potencialidades, as soluções existentes, geralmente, consideram um único usuário agindo como publicador. Ao lidar com múltiplos publicadores, elas podem levar a uma explosão combinatória de chaves criptográficas. As soluções projetadas visando a múltiplos publicadores, por sua vez, dependem de arquiteturas de redes específicas e/ou de mudanças nessas para operar. Nesta dissertação é proposta uma solução, apoiada em criptografia baseada em atributos, para controle de acesso a conteúdos. Nessa solução, o modelo de segurança é voltado a grupos de compartilhamento seguro, nos quais todos os usuários membros podem publicar e consumir conteúdos. Diferente de trabalhos anteriores, a solução proposta mantém o número de chaves proporcional ao de membros nos grupos e pode ser empregada em qualquer arquitetura ICN de forma gradual. A proposta é avaliada quanto ao custo de operação, à quantidade de chaves necessárias e à eficiência na disseminação de conteúdos. Em comparação às soluções existentes, ela oferece maior flexibilidade no controle de acesso, sem aumentar a complexidade do gerenciamento de chaves e sem causar sobrecustos significativos à rede.
One of the main challenges in Information-Centric Networking (ICN) is providing access control to content publication and retrieval. In spite of the potentialities, existing solutions often consider a single user acting as publisher. When dealing with multiple publishers, they may lead to a combinatorial explosion of cryptographic keys. Those solutions that focus on multiple publishers, on the other hand, rely on specific network architectures and/or changes to operate. In this dissertation, it is proposed a solution, supported by attribute-based encryption, for content access control. In this solution, the security model is focused on secure content distribution groups, in which any member user can publish to and retrieve from. Unlike previous work, the proposed solution keeps the number of cryptographic keys proportional to the number of group members, and may even be adopted gradually in any ICN architecture. The proposed solution is evaluated with respect to the overhead it imposes, number of required keys, and efficiency in the content dissemination. In contrast to existing solutions, it offers higher access control flexibility, without increasing key management process complexity and without causing significant network overhead.
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Bartow, Paul J. "Information retrieval /." Online version of thesis, 1991. http://hdl.handle.net/1850/12169.

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Lui, Chang. "Synatic Information Retrieval." Thesis, University of Ulster, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.516287.

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Dunlop, Mark David. "Multimedia information retrieval." Thesis, University of Glasgow, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.358626.

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Keim, Michelle. "Bayesian information retrieval /." Thesis, Connect to this title online; UW restricted, 1997. http://hdl.handle.net/1773/8937.

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Brucato, Matteo. "Temporal Information Retrieval." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2013. http://amslaurea.unibo.it/5690/.

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Buscaldi, Davide. "Toponym Disambiguation in Information Retrieval." Doctoral thesis, Universitat Politècnica de València, 2010. http://hdl.handle.net/10251/8912.

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In recent years, geography has acquired a great importance in the context of Information Retrieval (IR) and, in general, of the automated processing of information in text. Mobile devices that are able to surf the web and at the same time inform about their position are now a common reality, together with applications that can exploit this data to provide users with locally customised information, such as directions or advertisements. Therefore, it is important to deal properly with the geographic information that is included in electronic texts. The majority of such kind of information is contained as place names, or toponyms. Toponym ambiguity represents an important issue in Geographical Information Retrieval (GIR), due to the fact that queries are geographically constrained. There has been a struggle to nd speci c geographical IR methods that actually outperform traditional IR techniques. Toponym ambiguity may constitute a relevant factor in the inability of current GIR systems to take advantage from geographical knowledge. Recently, some Ph.D. theses have dealt with Toponym Disambiguation (TD) from di erent perspectives, from the development of resources for the evaluation of Toponym Disambiguation (Leidner (2007)) to the use of TD to improve geographical scope resolution (Andogah (2010)). The Ph.D. thesis presented here introduces a TD method based on WordNet and carries out a detailed study of the relationship of Toponym Disambiguation to some IR applications, such as GIR, Question Answering (QA) and Web retrieval. The work presented in this thesis starts with an introduction to the applications in which TD may result useful, together with an analysis of the ambiguity of toponyms in news collections. It could not be possible to study the ambiguity of toponyms without studying the resources that are used as placename repositories; these resources are the equivalent to language dictionaries, which provide the di erent meanings of a given word.
Buscaldi, D. (2010). Toponym Disambiguation in Information Retrieval [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/8912
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Books on the topic "Information retrival"

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Lin, Hongfei, Min Zhang, and Liang Pang, eds. Information Retrieval. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88189-4.

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Grossman, David A., and Ophir Frieder. Information Retrieval. Dordrecht: Springer Netherlands, 2004. http://dx.doi.org/10.1007/978-1-4020-3005-5.

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Fuhr, Norbert, ed. Information Retrieval. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-76981-8.

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Zhang, Shichao, Tie-Yan Liu, Xianxian Li, Jiafeng Guo, and Chenliang Li, eds. Information Retrieval. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01012-6.

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Wen, Jirong, Jianyun Nie, Tong Ruan, Yiqun Liu, and Tieyun Qian, eds. Information Retrieval. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-68699-8.

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Gker, Aye, and John Davies, eds. Information Retrieval. Chichester, UK: John Wiley & Sons, Ltd, 2009. http://dx.doi.org/10.1002/9780470033647.

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Braslavski, Pavel, Ilya Markov, Panos Pardalos, Yana Volkovich, Dmitry I. Ignatov, Sergei Koltsov, and Olessia Koltsova, eds. Information Retrieval. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41718-9.

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Dou, Zhicheng, Qiguang Miao, Wei Lu, Jiaxin Mao, and Guang Jia, eds. Information Retrieval. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-56725-5.

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Zhang, Qi, Xiangwen Liao, and Zhaochun Ren, eds. Information Retrieval. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31624-2.

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Hersh, William. Information Retrieval. New York, NY: Springer New York, 2009. http://dx.doi.org/10.1007/978-0-387-78703-9.

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Book chapters on the topic "Information retrival"

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Verma, Mukul Kirti, Rajesh Dwivedi, Ajay Kumar Mallick, and Ebenezer Jangam. "Dimensionality Reduction Technique on SIFT Feature Vector for Content Based Image Retrival." In Communications in Computer and Information Science, 383–94. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9181-1_34.

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van Rijsbergen, C. J. "Information retrieval and informative reasoning." In Computer Science Today, 549–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/bfb0015266.

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Klinke, Harald. "Information Retrieval." In Digital Humanities, 268–78. Stuttgart: J.B. Metzler, 2017. http://dx.doi.org/10.1007/978-3-476-05446-3_19.

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Shahi, Dikshant. "Information Retrieval." In Apache Solr, 39–56. Berkeley, CA: Apress, 2015. http://dx.doi.org/10.1007/978-1-4842-1070-3_3.

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Shekhar, Shashi, and Hui Xiong. "Information Retrieval." In Encyclopedia of GIS, 577. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_636.

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Harvey, Charles, and Jon Press. "Information Retrieval." In Databases in Historical Research, 147–87. London: Macmillan Education UK, 1996. http://dx.doi.org/10.1007/978-1-349-24392-1_6.

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Riggert, Wolfgang. "Information Retrieval." In Betriebliche Informationskonzepte, 75–126. Wiesbaden: Vieweg+Teubner Verlag, 2000. http://dx.doi.org/10.1007/978-3-322-89195-2_3.

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Carneiro, Davide, Paulo Novais, and José Neves. "Information Retrieval." In Conflict Resolution and its Context, 141–62. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06239-6_7.

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Amati, Giambattista. "Information Retrieval." In Encyclopedia of Database Systems, 1–6. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4899-7993-3_915-2.

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Darwish, Kareem. "Information Retrieval." In Natural Language Processing of Semitic Languages, 299–334. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-45358-8_10.

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Conference papers on the topic "Information retrival"

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Siagian, Pandapotan, and Albert Sagala. "Web-based ranking signature using cluster retrival similarity." In 2016 International Seminar on Application for Technology of Information and Communication (ISemantic). IEEE, 2016. http://dx.doi.org/10.1109/isemantic.2016.7873826.

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Mohanapriya, S., and M. Vadivel. "Automatic retrival of MRI brain image using multiqueries system." In 2013 International Conference on Information Communication and Embedded Systems (ICICES 2013). IEEE, 2013. http://dx.doi.org/10.1109/icices.2013.6508214.

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Ghosh, Somen, and Ajay Ghosh. "Content based retrival of malaria positive images from a clinical database." In 2013 IEEE Second International Conference on Image Information Processing (ICIIP). IEEE, 2013. http://dx.doi.org/10.1109/iciip.2013.6707605.

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Matsumura, Atsushi, Atsuhiro Takasu, and Jun Adachi. "Effect of dependency relationships and ordered co-occurrence of words on Japanese information retrival (poster session)." In the fifth international workshop on. New York, New York, USA: ACM Press, 2000. http://dx.doi.org/10.1145/355214.355243.

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Kvet, Michal, and Karol Matiasko. "Temporal data retrieval efficiency." In 2017 IEEE 14th International Scientific Conference on Informatics. IEEE, 2017. http://dx.doi.org/10.1109/informatics.2017.8327246.

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Taneja, Sanya, Richard Boyce, William Reynolds, and Denis Newman-Griffis. "Introducing Information Retrieval for Biomedical Informatics Students." In Proceedings of the Fifth Workshop on Teaching NLP. Stroudsburg, PA, USA: Association for Computational Linguistics, 2021. http://dx.doi.org/10.18653/v1/2021.teachingnlp-1.16.

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Sun, Bingjun, Prasenjit Mitra, and C. Lee Giles. "Independent informative subgraph mining for graph information retrieval." In Proceeding of the 18th ACM conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1645953.1646026.

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Wijnhoven, Fons, Edwin van den Belt, Eddy Verbruggen, and Paul van der Vet. "Internal Data Market Services: An Ontology-Based Architecture and Its Evaluation." In 2003 Informing Science + IT Education Conference. Informing Science Institute, 2003. http://dx.doi.org/10.28945/2599.

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Abstract:
On information markets, many suppliers and buyers of information goods exchange values. Some of these goods are data, whose value is created in buyer interactions with data sources. These interactions are enabled by data market services (DMS). DMS give access to one or several data sources. The major problems with the creation of information value in these contexts are (1) the quality of information retrievals and related queries, and (2) the complexity of matching information needs and supplies when different semantics are used by source systems and information buyers. This study reports about a prototype DMS (called CIRBA), which employs an ontology-based information retrieval system to solve semantic problems for a DMS. The DMS quality is tested in an experiment to assess its quality from a user perspective against a traditional data warehouse (with SQL) solution. The CIRBA solution gave substantially higher user satisfaction than the data warehouse alternative.
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"Information Retrieval." In 2021 Fifth International Conference on Information Retrieval and Knowledge Management (CAMP). IEEE, 2021. http://dx.doi.org/10.1109/camp51653.2021.9498026.

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Poulon, Astrid, and Christophe Vaudry. "Information retrieval." In the 15th French-speaking conference on human-computer interaction. New York, New York, USA: ACM Press, 2003. http://dx.doi.org/10.1145/1063669.1063713.

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Reports on the topic "Information retrival"

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Jha, Somesh, Vitaly Shmatikov, and Matthew Fredrikson. Private Information Retrieval. Fort Belvoir, VA: Defense Technical Information Center, December 2010. http://dx.doi.org/10.21236/ada536856.

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Knoblock, Craig A., Yigal Arens, and Chu-Nan Hsu. Cooperating Agents for Information Retrieval. Fort Belvoir, VA: Defense Technical Information Center, May 1994. http://dx.doi.org/10.21236/ada285887.

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Hoeferlin, David M., and Stephen A. Thorn. Crosslingual Audio Information Retrieval Development. Fort Belvoir, VA: Defense Technical Information Center, April 2009. http://dx.doi.org/10.21236/ada539725.

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Newitt, L. R., G. V. Haines, and R. L. Coles. The magnetic information retrieval program. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1990. http://dx.doi.org/10.4095/225655.

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Bader, Brett William, Peter Chew, Ahmed Abdelali, and Tamara Gibson Kolda. Cross-language information retrieval using PARAFAC2. Office of Scientific and Technical Information (OSTI), May 2007. http://dx.doi.org/10.2172/908061.

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Liu, Xiaoyong, and W. B. Croft. Statistical Language Modeling for Information Retrieval. Fort Belvoir, VA: Defense Technical Information Center, January 2005. http://dx.doi.org/10.21236/ada440321.

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Franz, Martin, J. S. McCarley, and Wei-Jing Zhu. English-Chinese Information Retrieval at IBM. Fort Belvoir, VA: Defense Technical Information Center, January 2006. http://dx.doi.org/10.21236/ada456312.

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Lynch, C. Using the Z39.50 Information Retrieval Protocol. RFC Editor, December 1994. http://dx.doi.org/10.17487/rfc1729.

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Newitt, L. R., and G. V. Haines. An interactive magnetic information retrieval program. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1985. http://dx.doi.org/10.4095/315221.

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Newitt, L. R., and G. V. Haines. An interactive magnetic information retrieval program. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1985. http://dx.doi.org/10.4095/225672.

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