Using collaborative filtering to weave an information tapestry
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IEEE Internet Computing
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Information Processing and Management: an International Journal
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NLDB '08 Proceedings of the 13th international conference on Natural Language and Information Systems: Applications of Natural Language to Information Systems
TagRank: A New Rank Algorithm for Webpage Based on Social Web
ICCSIT '08 Proceedings of the 2008 International Conference on Computer Science and Information Technology
Mobile information retrieval with search results clustering: Prototypes and evaluations
Journal of the American Society for Information Science and Technology
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WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Semantic annotation, indexing, and retrieval
Web Semantics: Science, Services and Agents on the World Wide Web
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EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Semantically enhanced Information Retrieval: An ontology-based approach
Web Semantics: Science, Services and Agents on the World Wide Web
Information retrieval in folksonomies: search and ranking
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
Hi-index | 12.05 |
Traditional search engines have become the most useful tools to search the World Wide Web. Even though they are good for certain search tasks, they may be less effective for others, such as satisfying ambiguous or synonym queries. In this paper, we propose an algorithm that, with the help of Wikipedia and collaborative semantic annotations, improves the quality of web search engines in the ranking of returned results. Our work is supported by (1) the logs generated after query searching, (2) semantic annotations of queries and (3) semantic annotations of web pages. The algorithm makes use of this information to elaborate an appropriate ranking. To validate our approach we have implemented a system that can apply the algorithm to a particular search engine. Evaluation results show that the number of relevant web resources obtained after executing a query with the algorithm is higher than the one obtained without it.