Content-based Document Recommender System for Aerospace Grey Literature: Experimental Testing and User Opinion Survey

  • K. Nageswara Rao
  • V.G. Talwar
DOI: https://doi.org/10.14429/djlit.31.4.1107
Keywords: Recommender systems, content-based document recommender system, CODORS, information retrieval, document retrieval

Abstract

The study aims to test content-based document recommender system (CODORS) with sample data to retrieve most relevant technical documents without necessarily matching title terms and closely related to particular search term(s). The CODORS system was put open for users to search and obtain recommendations with weighted relevance ranking and also allowed to compare the results obtained through general OPAC search engine for the same keywords. Based on the findings of the experimental testing and evaluation, some conclusions have been drawn:The results exhibited that the CODORS search provided many more relevant documents and increased the recall value as compared to general OPAC search and also revealed documents that were retrieved for a given query through OPAC search appeared at different places-top, middle or end of the ranked list of documents -generated through the CODORS search for the same query.

http://dx.doi.org/10.14429/djlit.31.4.1107

Published
2011-07-19
How to Cite
Rao, K. N., & Talwar, V. (2011). Content-based Document Recommender System for Aerospace Grey Literature: Experimental Testing and User Opinion Survey. DESIDOC Journal of Library & Information Technology, 31(4). https://doi.org/10.14429/djlit.31.4.1107
Issue
Vol 31 No 4 (2011): Semantic Web
Section
Papers

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