文章基本信息

标题：Content-based Document Recommender System for Aerospace Grey Literature: Experimental Testing and User Opinion Survey
其他标题：Content-based Document Recommender System for Aerospace Grey Literature: Experimental Testing and User Opinion Survey
作者：K. Nageswara Rao ; V.G. Talwar
期刊名称：DESIDOC Journal of Library & Information Technology
电子版ISSN：0976-4658
出版年度：2011
卷号：31
期号：4
DOI：10.14429/djlit.31.4.1107
语种：English
出版社：DESIDOC, Ministry of Defence, India
摘要：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
关键词：Recommender systems; content-based document recommender system; CODORS; information retrieval; document retrieval