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1

Paice, Chris. "Expert systems for information retrieval?" Aslib Proceedings 38, no. 10 (1986): 343–53. http://dx.doi.org/10.1108/eb051026.

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2

Zuva, Keneilwe. "Evaluation of Information Retrieval Systems." International Journal of Computer Science and Information Technology 4, no. 3 (2012): 35–43. http://dx.doi.org/10.5121/ijcsit.2012.4304.

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3

Salton, Gerard. "Expert systems and information retrieval." ACM SIGIR Forum 31, no. 1 (1997): 39–42. http://dx.doi.org/10.1145/263868.263873.

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4

Salton, G. "Expert systems and information retrieval." ACM SIGIR Forum 21, no. 3-4 (1987): 3–9. http://dx.doi.org/10.1145/30075.30076.

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5

Locatis, Craig. "Information Retrieval Systems and Learning." Performance Improvement Quarterly 2, no. 3 (2008): 4–15. http://dx.doi.org/10.1111/j.1937-8327.1989.tb00408.x.

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6

Seiden, Peggy, and Mark Kibbey. "Information Retrieval Systems for Microcomputers." Library Hi Tech 3, no. 1 (1985): 41–54. http://dx.doi.org/10.1108/eb047581.

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7

Rashmi, Ms. "Introduction to Information Retrieval Systems." International Journal on Recent and Innovation Trends in Computing and Communication 3, no. 4 (2015): 2051–54. http://dx.doi.org/10.17762/ijritcc2321-8169.150462.

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8

Megill, Kenneth A. "Text information and retrieval systems." Information Processing & Management 29, no. 1 (1993): 146. http://dx.doi.org/10.1016/0306-4573(93)90030-h.

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9

Cacheda, Fidel, and Javier Parapar. "Information Retrieval and Recommender Systems." JUCS - Journal of Universal Computer Science 21, no. (13) (2015): 1706–7. https://doi.org/10.3217/jucs-021-13.

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10

Sen, Procheta. "Proactive information retrieval." ACM SIGIR Forum 55, no. 2 (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 th
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11

Oliver, Ron. "Interactive information systems: information access and retrieval." Electronic Library 13, no. 3 (1995): 187–94. http://dx.doi.org/10.1108/eb045360.

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12

Kumar, Ram, and S. C. Sharma. "Information Retrieval System." International Journal of Technology Diffusion 9, no. 1 (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 ar
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13

Rorissa, Abebe. "Image retrieval: Benchmarking visual information indexing and retrieval systems." Bulletin of the American Society for Information Science and Technology 33, no. 3 (2008): 15–17. http://dx.doi.org/10.1002/bult.2007.bult1720330310.

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14

Valcarce, Daniel. "Information retrieval models for recommender systems." ACM SIGIR Forum 53, no. 1 (2019): 44–45. http://dx.doi.org/10.1145/3458537.3458545.

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Information retrieval addresses the information needs of users by delivering relevant pieces of information but requires users to convey their information needs explicitly. In contrast, recommender systems offer personalized suggestions of items automatically. Ultimately, both fields help users cope with information overload by providing them with relevant items of information. This thesis aims to explore the connections between information retrieval and recommender systems. Our objective is to devise recommendation models inspired in information retrieval techniques. We begin by borrowing ide
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15

D, Lande, Soboliev A, and Dmytrenko O. "Intelligent technologies in information retrieval systems." Artificial Intelligence 27, jai2022.27(1) (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 o
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16

Agosti, Maristella, and Franco Spilotro. "Design of personal information retrieval systems*." Information Services & Use 6, no. 4 (1986): 161–68. http://dx.doi.org/10.3233/isu-1986-6404.

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17

Llewellyn, Tony. "Capital allowances and information retrieval systems." Facilities 15, no. 9/10 (1997): 220–23. http://dx.doi.org/10.1108/02632779710178749.

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18

Chen, Hsinchun, and Vasant Dhar. "User misconceptions of information retrieval systems." International Journal of Man-Machine Studies 32, no. 6 (1990): 673–92. http://dx.doi.org/10.1016/s0020-7373(05)80107-5.

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19

O'Leary, Daniel E. "Internet-based information and retrieval systems." Decision Support Systems 27, no. 3 (1999): 319–27. http://dx.doi.org/10.1016/s0167-9236(99)00054-8.

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20

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 (2019): 868–74. http://dx.doi.org/10.5373/jardcs/v11/20192645.

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21

Thuraisingham, Bhavani. "Multilevel security for information retrieval systems." Information & Management 24, no. 2 (1993): 93–103. http://dx.doi.org/10.1016/0378-7206(93)90058-2.

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22

Azubuike, Abraham A., and Jackson S. Umoh. "Computerized information storage and retrieval systems." International Library Review 20, no. 1 (1988): 101–10. http://dx.doi.org/10.1016/0020-7837(88)90046-5.

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23

Efthimiadis, Efthimis N., David G. Hendry, Efthimis N. Efthimiadis, Pamela Savage-Knepshield, Carol Tenopir, and Peiling Wang. "Mental models of information retrieval systems." Proceedings of the American Society for Information Science and Technology 41, no. 1 (2005): 580–81. http://dx.doi.org/10.1002/meet.1450410186.

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24

Shi, Guoliang. "Artistic aspects of information retrieval systems." Proceedings of the American Society for Information Science and Technology 42, no. 1 (2006): n/a. http://dx.doi.org/10.1002/meet.14504201108.

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25

Drott, M. Carl. "Information retrieval systems: Theory and implementation." Journal of the American Society for Information Science 49, no. 7 (1998): 668–70. http://dx.doi.org/10.1002/(sici)1097-4571(19980515)49:7<668::aid-asi8>3.0.co;2-x.

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26

El Barbary, O. G., A. S. Salama, and El Sayed Atlam. "Granular information retrieval using neighborhood systems." Mathematical Methods in the Applied Sciences 41, no. 15 (2017): 5737–53. http://dx.doi.org/10.1002/mma.4610.

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27

Brooks, H. M. "Expert systems and intelligent information retrieval." Information Processing & Management 23, no. 4 (1987): 367–82. http://dx.doi.org/10.1016/0306-4573(87)90023-9.

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28

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

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29

Mosbah, Mawloud. "Query Refinement into Information Retrieval Systems." Journal of information and organizational sciences 47, no. 1 (2023): 133–51. http://dx.doi.org/10.31341/jios.47.1.7.

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Query, expressing the user need and requirement, has an important role, in aninformation retrieval system, for reaching a high accuracy search. In this paper, wepresent an overview of the different refinement operations that the query may undergo,in the sake to enhance performance of an information retrieval system, such as:automatic query formulation through words prevision, query reformulation, queryexpansion, and query optimization.
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30

Oliver, Ron, and Helen Oliver. "Information access and retrieval with hypermedia information systems." British Journal of Educational Technology 27, no. 1 (1996): 33–44. http://dx.doi.org/10.1111/j.1467-8535.1996.tb00141.x.

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31

Darwish, Kareem. "Arabic Information Retrieval." Foundations and Trends® in Information Retrieval 7, no. 4 (2014): 239–342. http://dx.doi.org/10.1561/1500000031.

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32

Chor, Benny, Eyal Kushilevitz, Oded Goldreich, and Madhu Sudan. "Private information retrieval." Journal of the ACM 45, no. 6 (1998): 965–81. http://dx.doi.org/10.1145/293347.293350.

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33

Carmel, David, Yoelle Maarek, and Aya Soffer. "XML and information retrieval." ACM SIGMOD Record 30, no. 1 (2001): 62–65. http://dx.doi.org/10.1145/373626.373705.

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34

Kraft, Donald H., and Frederick E. Petry. "Fuzzy information systems: managing uncertainty in databases and information retrieval systems." Fuzzy Sets and Systems 90, no. 2 (1997): 183–91. http://dx.doi.org/10.1016/s0165-0114(97)00085-7.

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35

DOMINICH, SÁNDOR. "INTERACTION INFORMATION RETRIEVAL." Journal of Documentation 50, no. 3 (1994): 197–212. http://dx.doi.org/10.1108/eb026930.

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36

Belew, Richard K. "Adaptive Information Retrieval." ACM SIGIR Forum 51, no. 2 (2017): 106–15. http://dx.doi.org/10.1145/3130348.3130359.

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37

van Zwol, Roelof, Stefan Rüger, Mark Sanderson, and Yosi Mass. "Multimedia information retrieval." ACM SIGIR Forum 41, no. 2 (2007): 77–82. http://dx.doi.org/10.1145/1328964.1328978.

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38

Manmatha, R., Stefan Rüger, and Alex Hauptmann. "Multimedia information retrieval." ACM SIGIR Forum 39, no. 2 (2005): 40–41. http://dx.doi.org/10.1145/1113343.1113352.

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39

Bennett, Paul N., Khalid El-Arini, Thorsten Joachims, and Krysta M. Svore. "Enriching information retrieval." ACM SIGIR Forum 45, no. 2 (2012): 60–65. http://dx.doi.org/10.1145/2093346.2093355.

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40

Downie, J. Stephen. "Music information retrieval." Annual Review of Information Science and Technology 37, no. 1 (2005): 295–340. http://dx.doi.org/10.1002/aris.1440370108.

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41

Abu El-Khair, Ibrahim. "Arabic information retrieval." Annual Review of Information Science and Technology 41, no. 1 (2007): 505–33. http://dx.doi.org/10.1002/aris.2007.1440410118.

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42

Ruthven, Ian. "Interactive information retrieval." Annual Review of Information Science and Technology 42, no. 1 (2009): 43–91. http://dx.doi.org/10.1002/aris.2008.1440420109.

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43

Guo, Tao, Ruida Zhou, and Chao Tian. "On the Information Leakage in Private Information Retrieval Systems." IEEE Transactions on Information Forensics and Security 15 (2020): 2999–3012. http://dx.doi.org/10.1109/tifs.2020.2981282.

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44

Petratos, Panagiotis. "Information Retrieval Systems: A Human Centered Approach." Interdisciplinary Journal of Information, Knowledge, and Management 2 (2007): 017–32. http://dx.doi.org/10.28945/97.

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45

Smith, Philip J., Deborah Krawczak, Steven J. Shute, and Mark H. Chignell. "Bibliographic information retrieval systems: increasing cognitive compatibility*." Information Services & Use 7, no. 4-5 (1987): 95–102. http://dx.doi.org/10.3233/isu-1987-74-502.

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46

KMathews, Litty, and S. Deepa Kanmani. "A Survey on Temporal Information Retrieval Systems." International Journal of Computer Applications 58, no. 4 (2012): 24–28. http://dx.doi.org/10.5120/9271-3461.

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47

Korfhage, Robert. "Book review: information storage and retrieval systems." XRDS: Crossroads, The ACM Magazine for Students 6, no. 5 (2000): 4. http://dx.doi.org/10.1145/345107.345115.

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48

White, Howard D. "Text Information Retrieval Systems. Charles T. Meadow." Library Quarterly 63, no. 1 (1993): 106–8. http://dx.doi.org/10.1086/602531.

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49

Carol Tenopir. "Online Systems for Information Access and Retrieval." Library Trends 56, no. 4 (2008): 816–29. http://dx.doi.org/10.1353/lib.0.0005.

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50

Krytskyy, T. I., N. V. Pasyechko, and L. V. Naumova. "Medical information retrieval systems in diabetes management." INTERNATIONAL JOURNAL OF ENDOCRINOLOGY (Ukraine) 20, no. 5 (2024): 370–74. http://dx.doi.org/10.22141/2224-0721.20.5.2024.1422.

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Background. Medical information retrieval is becoming more crucial as a way to support decision-making and improve access to knowledge and information for doctors and other specialists in the field. By the incorporation of medical domain knowledge for relevance evaluation, integrating the medical knowledge bases has the potential to enhance information retrieval performance. The system uses various search algorithms and techniques to provide accurate and comprehensive results to medical professionals and researchers. Medical information retrieval systems are particularly useful for healthcare
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