Organization Model of Semantic Document Repository and Search Techniques for Studying Information Technology
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32821
Organization Model of Semantic Document Repository and Search Techniques for Studying Information Technology

Authors: Nhon Do, Thuong Huynh, An Pham

Abstract:

Nowadays, organizing a repository of documents and resources for learning on a special field as Information Technology (IT), together with search techniques based on domain knowledge or document-s content is an urgent need in practice of teaching, learning and researching. There have been several works related to methods of organization and search by content. However, the results are still limited and insufficient to meet user-s demand for semantic document retrieval. This paper presents a solution for the organization of a repository that supports semantic representation and processing in search. The proposed solution is a model which integrates components such as an ontology describing domain knowledge, a database of document repository, semantic representation for documents and a file system; with problems, semantic processing techniques and advanced search techniques based on measuring semantic similarity. The solution is applied to build a IT learning materials management system of a university with semantic search function serving students, teachers, and manager as well. The application has been implemented, tested at the University of Information Technology, Ho Chi Minh City, Vietnam and has achieved good results.

Keywords: document retrieval system, knowledgerepresentation, document representation, semantic search, ontology.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1328011

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1666

References:


[1] Aly, A.A, "Using a query expansion technique to improve document retrieval", International Journal "Information Technologies and Knowledge" (2008).
[2] Dario Bonino, Fulvio Corno, Laura Farinetti, Alessio Bosca , "Ontology Driven Semantic Search", WSEAS Transaction on Information Science and Application, Issue 6, Volume 1, pp. 1597-1605 (2004).
[3] D. Genest, M. Chein, "An experiment in Document Retrieval using Conceptual Graph" , Proceeding of 5th ICCS Conference, Washington, USA, p 489-504 (1997).
[4] Harter, S.P., "A probabilistic approach to automatic keyword indexing", PhD thesis, Graduate Library, The University of Chicago, Thesis No. T25146.
[5] Henrik Bulskov Styltsvig, "Ontology-based Information Retrieval", A dissertation Presented to the Faculties of Roskilde University in Partial Fulfillment of the Requirement for the Degree of Doctor of Philosophy (2006).
[6] Henrik Eriksso, "The semantic-document approach to combining documents and ontologies", International Journal of Human-Computer Studies Volume 65, Issue 7, Pages 624-639 (2007)
[7] Kraaij, W., "Variations on Language Modeling for Information Retrieval", ACM SIGIR Forum (2005).
[8] Sanderson M., "Word Sense Disambiguation and Information Retrieval", Annual ACM Conference on Research and Development in Information Retrieval, Ireland Springer-Verlag New York, Inc (1994)
[9] Salton G., A. Wong, and C.S. Yang, "A Vector Space Model for Automatic Indexing", Communications of the ACM, 1975. 18(11): p. 613-620.
[10] Stokoe, C., M.P. Oakes, and J. Tait, "Word sense disambiguation in information retrieval revisited", Annual ACM Conference on Research and Development in Information Retrieval Toronto, Canada (2003).
[11] Thanh Tran, Philipp Cimiano, Sebastian Rudolph and Rudi Studer, "Ontology-Based Interpretation of Keywords for Semantic Search", The Semantic Web Lecture Notes in Computer Science, Volume 4825/2007, 523-536 (2007)
[12] Tzoukermann, E., J.L. Klavans, and C. Jacquemin, "Effective use of natural language processing techniques for automatic conflation of multi-word terms: the role of derivational morphology, part of speech tagging, and shallow parsing", SIGIR -97: Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval, p. 148-155 (1997)
[13] Vallez, M. and R. Pedraza-Jimenez, "Natural Language Processing in Textual Information Retrieval and Related Topics", I.S.S.o.t.P.F. University (2007).