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Using Thematic Contexts and Previous Solutions for Maintaining and Accessing Institutional Repositories
Keywords:
Institutional Repositories, Context-Based Search, Case-Based Reasoning, Information Retrieval, Information Access, Library Cataloger Support ToolsAbstract
Institutional Repositories are collections of digital resources organized to facilitate their long term access. Two fundamental issues that need to be addressed at the moment of implementing these repositories are their maintenance and search instruments. This article describes an intelligent tool whose goal is to overcome certain general limitations encountered in current mechanisms for managing Institutional Repositories. The novel aspects of the proposed tool are the use of previous examples to generate suggestions for cataloging incoming digital resources and the ability to refect a thematic context during the search process. The proposed tool applies casebased reasoning in combination with information retrieval techniques to take advantage of a large set of previously classified resources with the purpose of supporting the cataloger's task. The tool has been evaluated using a collection consisting of 9792 training examples from the SciELO electronic library and a test set containing 100 articles coming from diferent disciplines.
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References
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[19] Maguitman, A., Leake, D., & Reichherzer, T. (2005). Suggesting novel but related topics: towards context-based support for knowledge model extension. In Proceedings of IUI (pp. 207-214). New York, NY, USA : ACM Press.
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[2] Baeza-Yates R. & Ribeiro-Neto B. (2010). Modern Information Retrieval. Second Edition. Addison-Wesley.
[3] Baldonado, M. Q. W., & Winograd, T. (1997). SenseMaker: an information-exploration interface supporting the contextual evolution of a user’s interests. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 11-18). ACM Press.
[4] Buckland, M. (1992). Redesigning Library Services, A Manifesto. American Library Association, Chicago.
[5] Budzik, J., Hammond K. J., & Birnbaum L.(2001). Information Access in Context. Knowledge Based Systems, 14(1-2):37-53, Elsevier.
[6] Cecchini, R., Lorenzetti, C., Maguitman, A. & Brignole, N. B. (2010). Multiobjective Evolutionary Algorithms for Context-based Search. Journal of the American Society for Information Science and Technology, 61(6):1258-1274, John Wiley & Sons, Inc.
[7] Dini, M. A., Varela, M. A., Antúnez, V., Maguitman, A. & Herrera, L. (2010). Soporte Inteligente para el Mantenimiento y Acceso Contextualizado a Repositorios Institucionales. 8 a Jornada sobre la Biblioteca Digital Universitaria.
[8] Gospodnetic, O., Hatcher, E. & McCandless M. (2009). Lucene in Action (2nd ed.). Manning Publications.
[9] Holland, J. H. (1975). Adaptation in Natural and Artificial Systems, University of Michigan Press, Ann Arbor.
[10] Hulth, A., Karlgren, J., Jonsson, A., Boström, H. & Asker, L. (2001). Automatic Keyword Extraction Using Domain Knowledge. Computational Linguistics and Intelligent Text Processing, 2004/2001:472-482. Springer Verlag, Berlin.
[11] Jean, B. S., Rieh, S. Y., Yakel E., & Markey K. (2011). Unheard Voices: Institutional Repository End-Users. College & Research Libraries.
[12] Kraft, R., Chang, C. C., Maghoul, F., & Kumar, R. (2006). Searching with Context. In Proceedings of the 15th International Conference on the World Wide Web, pages 477-486, New York, NY, USA. ACM Press.
[13] Leake, D. (1996). CBR in Context: The Present and Future, In Leake, D., editor, Case-Based Reasoning: Experiences, Lessons, and Future Directions. 1-30, AAAI Press/MIT Press.
[14] Levy, D. M. & Marshall, C. C. (1995). Going digital: a look at assumptions underlying digital libraries. Communications of the ACM. 38(4): 77-84. New York, NY, USA. ACM Press.
[15] Lieberman, H. (1995). Letizia: An agent that assists Web browsing. In C. S. Mellish (Ed.), Proceedings IJCAI (pp. 924-929). Montreal, Quebec, Canada : Morgan Kaufmann publishers Inc.: San Mateo, CA, USA.
[16] Lorenzetti, C. M., & Maguitman, A. G.(2009). A Semi-Supervised Incremental Algorithm to Automatically Formulate Topical Queries. Information Sciences, 179(12):1881-1892. Special Issue on Web Search.
[17] Maglio, P. P., Barrett, R., Campbell, C. S., & Selker, T. (2000). SUITOR: an attentive information system. In Proceedings of the 5th international conference on intelligent user interfaces (pp. 169-176). ACM Press.
[18] Maguitman, A., Leake, D., Reichherzer, T., & Menczer, F. (2004). Dynamic extraction of topic descriptors and discriminators: Towards automatic context-based topic search. In Proceedings of CIKM (pp. 463-472). Washington, DC : ACM Press.
[19] Maguitman, A., Leake, D., & Reichherzer, T. (2005). Suggesting novel but related topics: towards context-based support for knowledge model extension. In Proceedings of IUI (pp. 207-214). New York, NY, USA : ACM Press.
[20] Rhodes, B. & Starner, T. (1996). The remembrance agent: A continuously running automated information retrieval system. In Proceedings of PAAM (pp. 487-495).
[21] Salton, G., Wong, A & Yang C. S. (1975). A Vector Space Model for Automatic Indexing, Communications of the ACM, 18 (11): 613-620, ACM Press.
[22] http://www.scielo.org.ar/. Accessed on August 7 2011.
[23] Sølvberg, I. T. (2001). Digital libraries and information retrieval, Lectures on information retrieval, Springer-Verlag New York, Inc., New York, NY.
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Published
2011-10-03
How to Cite
Delgado, P. H., Maguitman, A. G., Ferracutti, V. M., & Herrera, L. A. (2011). Using Thematic Contexts and Previous Solutions for Maintaining and Accessing Institutional Repositories. Journal of Computer Science and Technology, 11(02), p. 61–67. Retrieved from https://journal.info.unlp.edu.ar/JCST/article/view/669
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