Статті в журналах: "CANSIM (Information retrieval system)"

1

Monty, Vivienne. "CANSIM (Canadian Socioeconomic Information Management) System." Government Publications Review 18, no. 4 (July 1991): 405–6. http://dx.doi.org/10.1016/0277-9390(91)90038-y.

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2

Skinner, R., S. McFaull, J. Draca, M. Frechette, J. Kaur, C. Pearson, and W. Thompson. "Suicide and self-inflicted injury hospitalizations in Canada (1979 to 2014/15)." Health Promotion and Chronic Disease Prevention in Canada 36, no. 11 (November 2016): 243–51. http://dx.doi.org/10.24095/hpcdp.36.11.02.

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Introduction The purpose of this paper is to describe the trends and patterns of self-inflicted injuries, available from Canadian administrative data between 1979 and 2014/15, in order to inform and improve suicide prevention efforts. Methods Suicide mortality and hospital separation data were retrieved from the Public Health Agency of Canada (PHAC) holdings of Statistics Canada’s Canadian Vital Statistics: Death Database (CVS:D) (1979 to 2012); Canadian Socio-Economic Information Management System (CANSIM 2011, 2012); the Hospital Morbidity Database (HMDB) (1994/95 to 2010/11); and the Discharge Abstract Database (2011/12 to 2014/15). Mortality and hospitalization counts and rates were reported by sex, 5-year age groups and method. Results The Canadian suicide rate (males and females combined, all ages, age-sex standardized rate) has decreased from 14.4/100 000 (n = 3355) in 1979 to 10.4/100 000 (n = 3926) in 2012, with an annual percent change (APC) of –1.2% (95% CI: –1.3 to –1.0). However, this trend was not observed in both sexes: female suicide rates stabilized around 1990, while male rates continued declining over time—yet males still accounted for 75.7% of all suicides in 2012. Suffocation (hanging and strangulation) was the primary method of suicide (46.9%) among Canadians of all ages in 2012, followed by poisoning at 23.3%. In the 2014/15 fiscal year, there were 13 438 hospitalizations in Canada (excluding Quebec) associated with self-inflicted injuries—over 3 times the number of suicides. Over time females have displayed consistently higher rates of hospitalization for self-inflicted injury than males, with 63% of the total. Poisoning was reported as the most frequent means of self-inflicted harm in the fiscal year 2014/15, at 86% of all hospitalizations. Conclusion Suicides and self-inflicted injuries continue to be a serious—but preventable— public health problem that requires ongoing surveillance.

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Kumar, Ram, and S. C. Sharma. "Information Retrieval System." International Journal of Technology Diffusion 9, no. 1 (January 2018): 1–10. http://dx.doi.org/10.4018/ijtd.2018010101.

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Information Retrieval Systems (IRS) have dramatically changed the ways how people acquire information for their need. Information Retrieval (IR) enables user to find relevant document from collection of countless resources. This article presents an overview of IRS. Objectives of this article is to answer all the basic and specific questions related to IRS. In contrast to other review papers, the authors provide a complete understanding of IR in single paper. Starting from definition and importance it covers retrieval process, performance issues, and comparison among various approaches. This article also includes description of different models along with analysis of their merits and demerits. This article proposes a list of challenges, still unanswered by existing systems. Before offering a conclusion, the major applications of IR are also listed.

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4

Abimbola, Bola. "Intelligent Information Retrieval System." International Journal of Artificial Intelligence and Machine Learning 2, no. 1 (January 18, 2022): 71. http://dx.doi.org/10.51483/ijaiml.2.1.2022.71-74.

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Choi, Okkyung, Kangseok Kim, Duksang Wang, Hongjin Yeh, and Manpyo Hong. "Personalized Mobile Information Retrieval System." International Journal of Advanced Robotic Systems 9, no. 1 (January 1, 2012): 11. http://dx.doi.org/10.5772/50910.

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Building a global Network Relations with the internet has made huge changes in personal information system and even comments left on a webpage of SNS(Social Network Services) are appreciated as important elements that would provide valuable information for someone. Social Network is a relation between individuals or groups, represented in a graph model, which converts the concept of psychological and social relations into a logical structure by using node and link. But, most of the current personalized systems on the basis of Social Network are built and constructed mainly in the PC environment, and the systems are neither designed nor implemented in mobile environment. Hence, the objective of this study is to propose methods of providing Personalized Mobile Information Retrieval System using NFC (Near Field Communication) Smartphone, which will be then used for Smartphone users. Besides, this study aims to verify its efficiency through a comparative analysis of existing studies.

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Hong, Seok-Joo, and Young-Bae Park. "Information Retrieval System for R2SS." Journal of the Korea Contents Association 9, no. 12 (December 28, 2009): 39–51. http://dx.doi.org/10.5392/jkca.2009.9.12.039.

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7

Md. Kowsher, Imran Hossen, and SkShohorab Ahmed. "Bengali Information Retrieval System(BIRS)." International Journal on Natural Language Computing 8, no. 5 (October 31, 2019): 1–12. http://dx.doi.org/10.5121/ijnlc.2019.8501.

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Tewari, Ashish Kumar, Rashi, Gulshan Wadhwa, Sanjeev Kumar Sharma, and Chakresh Kumar Jain. "BIRS – Bioterrorism Information Retrieval System." Bioinformation 9, no. 2 (January 18, 2013): 112–15. http://dx.doi.org/10.6026/97320630009112.

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SHIRAHASHI, Akihiro. "Information retrieval system through Internet." Journal of Information Processing and Management 37, no. 1 (1994): 19–26. http://dx.doi.org/10.1241/johokanri.37.19.

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Davcev, Danco, Dusan Cakmakov, and Vanco Cabukovski. "Distributed multimedia information retrieval system." Computer Communications 15, no. 3 (April 1992): 177–84. http://dx.doi.org/10.1016/0140-3664(92)90078-s.

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11

Chkiwa, Mounira, Anis Jedidi, and Faiez Gargouri. "Semantic / Fuzzy Information Retrieval System." International Journal of Information Technology and Web Engineering 12, no. 1 (January 2017): 37–56. http://dx.doi.org/10.4018/ijitwe.2017010103.

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In this paper, the authors present an overall description of their information retrieval system which makes a practical collaboration between Semantic Web and Fuzzy logic in order to have profit from their advantages in the information retrieval domain. Their system is dedicated for kids, for this reason the semantic/fuzzy collaboration materialized must be in the background of the information retrieval process because such category of users cannot certainly control semantic web technologies neither fuzzy logic commands. In this paper, the authors present the different services proposed by their system and how they use Semantic Web and Fuzzy logic to develop it. Evaluation tests of the system using universal measures show clearly its efficiency.

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12

Gudi, Anirudh. "Hypertext Based Information Retrieval System." IETE Technical Review 12, no. 4 (July 1995): 261–67. http://dx.doi.org/10.1080/02564602.1995.11416538.

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13

Lucarella, D., and R. Morara. "FIRST: Fuzzy Information Retrieval SysTem." Journal of Information Science 17, no. 2 (April 1991): 81–91. http://dx.doi.org/10.1177/016555159101700202.

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14

Zelitchenko, Alexander I. "Information retrieval expert system “matchmaker”." Computers in Human Behavior 8, no. 4 (December 1992): 281–96. http://dx.doi.org/10.1016/0747-5632(92)90025-a.

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15

Escobedo, Richard, Scott D. G. Smith, and Thomas P. Caudell. "A neural information retrieval system." International Journal of Advanced Manufacturing Technology 8, no. 4 (July 1993): 269–73. http://dx.doi.org/10.1007/bf01748637.

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16

Hiromichi, F. "Knowledge based information retrieval system." Expert Systems with Applications 9, no. 3 (1995): IV—V. http://dx.doi.org/10.1016/0957-4174(95)98747-7.

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Xu, Hong. "Multimodal bird information retrieval system." Applied and Computational Engineering 53, no. 1 (March 28, 2024): 96–102. http://dx.doi.org/10.54254/2755-2721/53/20241282.

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Multimodal bird information retrieval system can help people popularize bird knowledge and help bird conservation. In this paper, we use the self-built bird dataset, the ViT-B/32 model in CLIP model as the training model, python as the development language, and PyQT5 to complete the interface development. The system mainly realizes the uploading and displaying of bird pictures, the multimodal retrieval function of bird information, and the introduction of related bird information. The results of the trial run show that the system can accomplish the multimodal retrieval of bird information, retrieve the species of birds and other related information through the pictures uploaded by the user, or retrieve the most similar bird information through the text content described by the user.

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18

Hou, Yong. "Mathematical formula information retrieval system." Journal of Computational Methods in Sciences and Engineering 23, no. 6 (December 15, 2023): 2949–73. http://dx.doi.org/10.3233/jcm-226961.

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Design and implementation of the system for retrieving information about mathematical formulas – MFIRS. The structure of the system is mainly divided into the modules: input normalization, mathematical formula unification, mathematical formula encoding, text information feature extraction, mathematical formula feature extraction, mathematical formula indexing, retrieval and ranking. A method for extracting mathematical formulas and keywords based on FastText word embedding technology is proposed. This method can be used not only to get the structural features of the formula, but also to facilitate the calculation of the similarity of the formula by the vector result. At the same time, the model introduces the semantic features of context-rich mathematical formulas to improve the domain correlation of search results. The MathRetEval dataset was created based on about 7.9 × 105 arXiv documents and about 1.5 × 108 mathematical formulas. The scalability of the system is verified using this data set. The mathematical formulas can be written in the language TEX or MathML. When queried in the TEX language, it can be converted to a tree representation of the MathML representation and then indexed. This MFIRS is an information retrieval system for mathematical formulas with the features of mathematical perception, which can use the search for the similarity of partial formulas.

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YOKOYAMA, Kiyoshi, Hidenori MURAKAMI, and Nobuyuki FUKASAWA. "Toward intelligent information system. (4). Expert system for information retrieval." Journal of Information Processing and Management 32, no. 3 (1989): 223–34. http://dx.doi.org/10.1241/johokanri.32.223.

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Bovey, J. D. "A graphical retrieval system." Journal of Information Science 19, no. 3 (June 1993): 179–87. http://dx.doi.org/10.1177/016555159301900302.

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21

McWhirr, Alan. "GRS (General Retrieval System): a retrieval system for use in the humanities." Program 20, no. 3 (March 1986): 275–88. http://dx.doi.org/10.1108/eb046942.

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22

Niki, Kazuhisa. "Self-organized Information Retrieval System: SIR." Brain & Neural Networks 1, no. 1 (1994): 27–34. http://dx.doi.org/10.3902/jnns.1.27.

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23

Kim, Jae-Hoon, and Hyung-Chul Kim. "Information Retrieval System for Mobile Devices." Journal of the Korean Society of Marine Engineering 33, no. 4 (May 31, 2009): 569–77. http://dx.doi.org/10.5916/jkosme.2009.33.4.569.

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24

ZAKI, U., M. MEMON, D. N. HAKRO, K. U. R. KHOUMBATI, M. HAMEED,, M. A. ZAKI, and G. NABI. "Implementation Challenges in Information Retrieval System." SINDH UNIVERSITY RESEARCH JOURNAL -SCIENCE SERIES 51, no. 02 (June 22, 2019): 339–44. http://dx.doi.org/10.26692/sujo/2019.6.55.

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Angdresey, Apriandy, Miguel Angelo Lamongi, and Rinaldi Munir. "Information Retrieval System in the Bible." CogITo Smart Journal 7, no. 1 (June 30, 2021): 111. http://dx.doi.org/10.31154/cogito.v7i1.300.111-120.

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Information retrieval is used to search for relevant documents so that they can be obtained quickly and precisely. There are many Christians who want to study the gospel. However, often experience problems in finding the Gospel verse and topics dealing with the need to search by the user. Therefore, have to search individually, each verse in the four Gospels to find the topic or verse that the user wants to find out. In this study, the authors used the Bible verses in the Gospels as documents, so that these verses could be searched for the level of relevance or similarity to the entered keywords. Furthermore, to determine the level of relevance between documents and keywords is calculated using the Vector Space Model. Based on the application that has been successfully built, the application can be show 10 documents related to the keywords that are searched and sorted from the most relevant, with the highest similarity value, namely 78.65%.Keywords - Information Retrieval, Vector Space Model, Bible.

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Gao, Ruoyuan. "Toward a fairer information retrieval system." ACM SIGIR Forum 55, no. 1 (June 2021): 1–2. http://dx.doi.org/10.1145/3476415.3476429.

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With the increasing popularity and social influence of information retrieval (IR) systems, various studies have raised concerns on the presence of bias in IR and the social responsibilities of IR systems. Techniques for addressing these issues can be classified into pre-processing , in-processing and post-processing. Pre-processing reduces bias in the data that is fed into machine learning models. In-processing encodes fairness constraints as a part of the objective function or learning process. Post-processing operates as a top layer over the trained model to reduce the presentation bias exposed to users. This dissertation explored ways to bring the pre-processing and post-processing approaches, together with the fairness-aware evaluation metrics, into a unified framework as an attempt to break the vicious cycle of bias and improve fairness in IR. We first investigated the existing bias presented in search engine results. Specifically, we focused on the top-k fairness ranking in terms of statistical parity fairness and disparate impact fairness definitions. With Google search and a general purposed text cluster as a lens, we explored several topical diversity fairness ranking strategies to understand the relationship between relevance and fairness in search results. Our experimental results showed that different fairness ranking strategies resulted in distinct utility scores and performed differently with distinct datasets. Second, to further investigate the relationship of data and fairness algorithms, we developed a statistical framework that was able to facilitate various analysis and decision making. Our framework could effectively and efficiently estimate the domain of data and solution space. We derived theoretical expressions to identify the fairness and relevance bounds for data of different distributions, and applied them to both synthetic datasets and real world datasets. We presented a series of use cases to demonstrate how our framework was applied to associate data and provide insights to fairness optimization problems. Third, we proposed an evaluation metric FAIR for the ranking results that encoded fairness, diversity, novelty and relevance. This metric offered a new perspective of evaluating fairness-aware ranking results. Based on this metric, we developed an effective ranking algorithm that jointly optimized for fairness and utility. Our experiments showed that our new metric was able to highlight results that achieved good user utility and fair information exposure at the same time. We showed how FAIR metric related to existing metrics through correlation analysis and case studies, and demonstrated the effectiveness of our FAIR-based algorithm.

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Lata, Suman, and Ajmer Kundu. "Wheat Production Information Retrieval System (WPIRS)." International Journal of Computer Applications 58, no. 2 (November 15, 2012): 16–19. http://dx.doi.org/10.5120/9253-3422.

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Kulkarni, D. R., and R. R. Bharucha. "READFAST — an online information retrieval system." Program 20, no. 3 (March 1986): 314–19. http://dx.doi.org/10.1108/eb046945.

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Ertwine, Robyn, and Beatrice Jakubowski. "CHID: An Automated Information Retrieval System." Diabetes Educator 12, no. 1 (January 1986): 55–60. http://dx.doi.org/10.1177/014572178601200114.

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The Combined Health Information Database (CHID) is an automated information system designed for health care educators and other health professionals. It contains 20,000 references to jour nal articles, fact sheets, brochures, audiovisual materials, health program descriptions, and other health-related information. Topics include diabetes, arthritis, digestive diseas es, high blood pressure, and health promotion and health education. Access to this information is available nationwide through a subscription service. The information included in CHID can be searched and retrieved quickly by computer, and the results can be orga nized and prepared according to the specific needs of the user.

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Shu-dong, Shi, and Li Zhi-tang. "A high-speed information retrieval system." Wuhan University Journal of Natural Sciences 9, no. 4 (July 2004): 425–28. http://dx.doi.org/10.1007/bf02830436.

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31

Aparna, T., Shivani D, Pratiksha B, Nuzzath Tahreen, and Anusha T. "Publications Information Retrieval and Management System." International Journal for Research in Applied Science and Engineering Technology 11, no. 7 (July 31, 2023): 810–15. http://dx.doi.org/10.22214/ijraset.2023.54661.

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Abstract: In a world where technology is advancing rapidly, it is a difficult task to manually maintain research profiles in any educational institution. Faculty have to go through an exhaustive ordeal to keep up to pace with the ever-changing demands of the publication committees. Hence, there is a significant need for an interface allowing researchers to easily sort, maintain and download their list of publications with minimum work from the user end. This paper attempts to set up an interface that would use web scraping with selenium and python modules to link a researcher’s list of publications present on Google Scholar to a PostgreSQL database and Excel application, allowing them to access and manipulate their research profiles in minimal steps

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Bedi, P., and S. Chawla. "Agent Based Information Retrieval System Using Information Scent." Journal of Artificial Intelligence 3, no. 4 (September 15, 2010): 220–38. http://dx.doi.org/10.3923/jai.2010.220.238.

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Shen, Jin Xing. "Ontology-Based Semantic Retrieval for Management Information System." Applied Mechanics and Materials 278-280 (January 2013): 2069–72. http://dx.doi.org/10.4028/www.scientific.net/amm.278-280.2069.

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In order to achieve semantic retrieval for scientific research information in WWW, this paper applies an ontology-based framework to information retrieval system for management information system. After analyze the limitations of traditional method, bring a semantic search forward, and mainly introduce the thought of the semantic retrieval as well as the way to constitute ontology entity and the language that describes it. Moreover, semantic retrieval system based on ontology is also given. The application to retrieve project information shows that the framework can overcome the localization of other ontology’s models, and this research facilitates the semantic retrieval of management information through semantic retrieval concepts on the Semantic Web.

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Li, Li, Wei Jiang Li, and Yuan Yuan Fan. "Topic-Oriented Information Retrieval." Advanced Materials Research 989-994 (July 2014): 4845–50. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.4845.

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With the rapid development of Internet, more and more information has been displayed to people. More and more researcher pay more attention to how to find useful information from this huge information ocean. We design the topic-oriented information retrieval system in order to overcome the drawback of generic crawler. The system retrieves topic information efficiently and helps user get useful information rapidly and exactly.

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Zhang, Shu Dong, and Yan Chen. "Research on Domain Ontology-Based Intelligent Information Retrieval System." Key Engineering Materials 460-461 (January 2011): 300–304. http://dx.doi.org/10.4028/www.scientific.net/kem.460-461.300.

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Domain ontology introduces a new theory and method for information retrieval. In this paper, we analyze the deficiencies of traditional information retrieval and explore the relationship between domain ontology and information retrieval, as well as the basic design ideas of information retrieval based on domain ontology. Finally we present a domain ontology-based intelligent information retrieval system, so that the information retrieval can be promoted from the keyword level to the semantic level. With the rapid development of the national economy and the growth of information resources, traditional methods relying on the browser, database fields, keyword matching, or even manual retrieval query has become increasingly difficult to meet people's information retrieval needs. How to quickly and accurately identify the needed information resources has become a urgent question in front of us. Information retrieval is a technology which can find out the relevant information the user needs from a collection of large amounts of information. It has experienced manual retrieval, computer retrieval stage, now it has developed to the network and intelligent stage. The objects of information retrieval extend from a relative closed, stable and consistent, centrally managed information content by an independent database to an open, dynamic, quickly update, widely distributed, and loosely managed web content; the users of information retrieval also spread from professional intelligence agent to the common including government officials, businessmen, managers, teachers, students, professionals, etc. They ask for the higher and more diverse requirements from the results to the manner of information retrieval. Adapting to the need for network, intelligence and personalization is a new trend of information retrieval technology.

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Lokhande, Kalyani, and Dhanashree Tayade. "English-Marathi Cross Language Information Retrieval System." International Journal of Advanced Research in Computer Science and Software Engineering 7, no. 8 (August 30, 2017): 112. http://dx.doi.org/10.23956/ijarcsse.v7i8.34.

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Nowadays, diﬀerent types of content in diﬀerent languages are available on World Wide Web and their usage is increasing rapidly. Cross Language Information Retrieval (CLIR) deals with retrieval of documents in another language than the language of the requested query. Various researchers worked on Cross Language Information Retrieval systems for Indian languages using diﬀerent translation approaches. There is still CLIR system to be developed which allow user to retrieve Marathi documents when English query is given. In the proposed English to Marathi Cross Language Information Retrieval system, translation is based on query translation approach. The proposed system retrieves Marathi documents depending on matching terms in query. The performance of the proposed system is improved by query pre-processing and query expansion using WordNet.

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Yu, Xiao Qing, Wen Gen Wang, Jian Hua Shi, and Yun Hui Wang. "An Information Retrieval System Based on Portable Device." Advanced Materials Research 712-715 (June 2013): 2706–11. http://dx.doi.org/10.4028/www.scientific.net/amr.712-715.2706.

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Information retrieval is the activity to organize information in a certain way, and according to the users demand to find out the related information from a collection of resources. Retrieval process and technology can be based on metadata or full-text indexing. Most of the relevant information retrieval systems are devised on the computer. However, with the highly development of the embedded technology, some popular application have been developed on the platform. In this paper, we will introduce an information retrieval system on the iOS platform which is more convenient, practical, and effective compared with the traditional system. And we will introduce an application based on this system design. The experiments shown that this system was exactly effective utilized to retrieval audio information.

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Sen, Procheta. "Proactive information retrieval." ACM SIGIR Forum 55, no. 2 (December 2021): 1–2. http://dx.doi.org/10.1145/3527546.3527576.

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Users interact with digital systems with some underlying tasks in their minds. In our research scope, a task can be either single or multi-staged. A single-staged task is associated with a single information need, whereas a multi-staged one is associated with more than one information needs. An example of a single-staged task is suggesting related papers to an author while they are writing a section of the research papers. An example of a multi-staged task is planning for a vacation, where the different underlying information needs could be 'places to visit', 'booking accommodation' etc. In the process of accomplishing their task objectives, a user often needs to interact with an information retrieval (IR) system to address one or more information needs. For instance, for writing a research paper on a chosen topic, a user needs to look for existing research work related to the topic. Traditional IR systems do not take into account a user's task intent while showing search results to the user. In our work, we propose a methodology towards developing next generation IR systems (i.e. proactive IR systems) which seek to anticipate the task intent of a user from their interactions with digital systems in order to proactively suggest potentially relevant information sources to assist them to complete their tasks. Specifically speaking, in this PhD, we proposed an embedding approach that captures the task semantics from the interactions of a user with a digital system (e.g. laptop, desktop, smartphone etc.). The proposed embedding approach is then applied for the downstream tasks of providing proactive suggestions in both single and multi staged scenarios. For the single-staged task, we propose a simulation setup to simulate a user's reading and writing interactions in a desktop environment. For the multi-staged task, we focus on web search sessions where a user can have multiple information needs corresponding to a search task. We also proposed a reproducible evaluation framework to compare between different proactive suggestion models. Awarded by : Dublin City University, Ireland on 10 August 2021. Supervised by : Gareth Jones. Available at : https://procheta.github.io/sprocheta/Thesis.pdf.

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Putri, Salsa Amalia, Yunus Winoto, and Rohanda Rohanda. "Pemetaan penelitian information retrieval system menggunakan VOSviewer." Informatio: Journal of Library and Information Science 3, no. 2 (May 31, 2023): 93. http://dx.doi.org/10.24198/inf.v3i2.46646.

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Анотація:

Information retrieval systems help filter information, so that the process of finding suitable information becomes fast and precise, but there are ways to find more effectively and efficiently with Information retrieval systems using bibliometric methods with the VOSviewer application. The research objectives are to map the trends of research results on the topic of information retrieval system in the library, to map the research results on the topic of information retrieval system in the library based on co-authorship, and to map the research results on the topic of information retrieval system in the library based on co-occurrence. The research method uses descriptive bibliometric analysis by using the Scopus scientific journal database. The results of research on the topic of information retrieval systems in libraries are fluctuating where the most research results occurred in 2008 with publications totaling 13 articles and the lowest publications were seen in 2010 and 2014 with only 1 article produced. The level of author productivity is at 13 authors who produce a total of 2 articles. Co-authorship analysis is useful to see the mapping of research topics through relationships or collaborations between authors. The number of authors analyzed is 278, of which there are only 13 authors who show relationships between other authors. Co-occurrence analysis is useful for displaying bibliometric networks between keywords in a visual form. There are 326 keywords taken and 18 keywords have an occurrence relationship. Based on the bibliometric analysis conducted, it can be seen the distribution of research topics related to information retrieval systems in libraries, including research keywords that are still rarely researched, such as metadata and user studies. This can be used as an opportunity for further research topics.

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Jena, Gouranga Charan, and Siddharth Swarup Rautaray. "A comprehensive survey on cross-language information retrieval system." Indonesian Journal of Electrical Engineering and Computer Science 14, no. 1 (April 1, 2019): 127. http://dx.doi.org/10.11591/ijeecs.v14.i1.pp127-134.

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Cross language information retrieval (CLIR) is a retrieval process in which the user fires queries in one language to retrieve information from another (different) language. The diversity of information and language barriers are the serious issues for communication and cultural exchange across the world. To solve such barriers, Cross language information retrieval system, are nowadays in strong demand. CLIR is a subset of Information Retrieval (IR) system. Information Retrieval deals with finding useful information from a large collection of unstructured, structured and semi-structured data to a user query where the query is a set of keywords. Information Retrieval can be classified into different classes such as Monolingual information retrieval, Bi-Lingual Information Retrieval, Multilingual information retrieval and Cross language information retrieval. This paper focuses on the various IR variants and techniques used in CLIR system. Further, based on available literature, a number of challenges and issues in CLIR have been identified and discussed. It gives an overview of the advantages, limitations, tools available in CLIR research. It also describes new application areas of CLIR such as medical, multimedia, question answering system etc. The need for exploring and building more specialized information system that enable speakers of an Odia language to discover valuable information beyond linguistic and cultural barriers. This study is aimed at building an experimental CLIR system between one of the under-resourced language (i.e. Odia) and one of the most commonly used online language (i.e. English) in future.

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Kovalcik, Justin, and Mike Villalobos. "Automated Storage & Retrieval System." Information Technology and Libraries 38, no. 4 (December 16, 2019): 114–24. http://dx.doi.org/10.6017/ital.v38i4.11273.

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The California State University, Northridge (CSUN) Oviatt Library was the first library in the world to integrate an automated storage and retrieval system (AS/RS) into its operations. The AS/RS continues to provide efficient space management for the library. However, added value has been identified in materials security and inventory as well as customer service. The concept of library as space, paired with improved services and efficiencies, has resulted in the AS/RS becoming a critical component of library operations and future strategy. Staffing, service, and security opportunities paired with support and maintenance challenges, enable the library to provide a unique critique and assessment of an AS/RS.

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Jones, Kevin P., and Colin L. M. Bell. "MORPHS—an intelligent retrieval system." Aslib Proceedings 38, no. 3 (March 1986): 71–79. http://dx.doi.org/10.1108/eb051000.

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43

Beitzel, Steven M., Eric C. Jensen, Abdur Chowdhury, David Grossman, Ophir Frieder, and Nazli Goharian. "Fusion of effective retrieval strategies in the same information retrieval system." Journal of the American Society for Information Science and Technology 55, no. 10 (2004): 859–68. http://dx.doi.org/10.1002/asi.20012.

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Wu, Feng, Yanting Ji, and Wenping Shi. "Design of a Computer-Based Legal Information Retrieval System." Computational Intelligence and Neuroscience 2022 (May 12, 2022): 1–10. http://dx.doi.org/10.1155/2022/6942773.

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In today’s society, people’s lives are increasingly inseparable from computer information. Due to the continuous improvement of technology and the rapid development of internet technology, the network environment is becoming more and more complex, which makes it easy to cause loopholes in the information retrieval system when people use the network. Therefore, it is especially important to search for legal knowledge by computer. In order to adapt to this change and demand, we need a retrieval system to provide the corresponding search function, legal information content, and management and other services, so as to achieve the purpose of computer legal information retrieval. The legal information retrieval system is computer based, draws conclusions from the analysis of relevant data, and then applies them to judicial trial cases, criminal investigations, and other fields to provide a reference for relevant legal issues. The system is designed to combine computer technology with a criminal investigation and other fields, and then analyze the data to draw the corresponding conclusions. The retrieval algorithms used are mainly image and content retrieval algorithms, and image retrieval algorithms mainly use image segmentation technology, while content retrieval algorithms mainly use the cuckoo algorithm. At present, the information construction and economic and social development in China have become one of the issues of common concern and need to be solved by all countries in the world. The study of the legal information retrieval system is of great importance in the construction of information technology and the development of economic society.

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Waldstein, Robert K. "SLIMMER—A UNIX™ System‐Based Information Retrieval System." Reference Services Review 16, no. 1/2 (January 1988): 69–76. http://dx.doi.org/10.1108/eb049012.

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Liu, Na, and Kun Liu. "Mobile Agents Build Web Information Retrieval System." Applied Mechanics and Materials 543-547 (March 2014): 3373–76. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.3373.

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In recent years, mobile agent has always been the hot spot of the academic research, this paper introduces the concept of mobile agent, mobile agent system architecture and key technologies, combined with the mobile technology and web information retrieval technology, design a model of information retrieval system based on mobile agent, and expounds the key technology to realize the model needs to solve.

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KumarKatiyar, Vijay, and Dalip Kamboj. "TIRS: SMS based Transportation Information Retrieval System." International Journal of Computer Applications 76, no. 12 (August 23, 2013): 15–19. http://dx.doi.org/10.5120/13299-0757.

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Radhouani, Saïd, Claire-Lise Mottaz Jiang, and Gilles Falquet. "FlexIR: a Domain-Specific Information Retrieval System." Polibits 39 (June 30, 2009): 27–31. http://dx.doi.org/10.17562/pb-39-4.

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T, Jyothi. "Efficient Information Retrieval System for Cloud Environments." IJARCCE 6, no. 4 (April 30, 2017): 312–15. http://dx.doi.org/10.17148/ijarcce.2017.6459.

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Zahra, Syeda Binish. "Desktop Based: Off-line Information Retrieval System." International Journal for Electronic Crime Investigation 2, no. 4 (December 7, 2018): 4. http://dx.doi.org/10.54692/ijeci.2018.020423.

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Information retrieval is rapidlydeveloping field and there are many changes are introduced day by day in traditional techniques for IR. IR system is intended to evaluate examine and accumulate the sources of information and get back those that match user's requirement. The need of today's fast moving life is to get maximum information but within minimum time. For getting maximum information in minimum time requires more efforts. The main functionality of IR is to provide access of documents (that document may be in collection of thousand, or millions). With the help of an appropriate description, user can recover any one document from a collection of documents. In this paper I describe my IR system which retrieves information from any directory and this information may be in terms of image, audio or in text form. The selection of good features also allows the space, time and costs of the retrieval process to be reduced. Two documents may be considered similar in this system if they have same name and places in different folders or directories. To explore the retrieval process from that system, I used Apache Lucene with JAVA implemented in IntelliJ.

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