Author/Authors :
WANG, Yan Beijing University of Technology - International WIC Institute, China , WANG, Cong Beijing University of Technology - International WIC Institute, China , ZENG, Yi Beijing University of Technology - International WIC Institute, China , HUANG, Zhisheng Vrije University Amsterdam - Knowledge Representation and Reasoning Group, Netherlands , Momtchev, Vassil Sirma Group - Ontotext AD, Bulgaria , Andersson, Bo AstraZeneca R D, Sweden , REN, Xu Beijing University of Technology - International WIC Institute, China , ZHONG, Ning Beijing University of Technology - International WIC Institute, China , ZHONG, Ning Maebashi Institute of Technology - Department of Life Science and Informatics, Japan
Abstract :
Literature searches on the Web result in great volumes of query results. A model is presented here to refine the search process using user interests. User interests are analyzed to calculate semantic similarity among the interest terms to refine the query. Traditional general purpose similarity measures may not always fit a domain specific context. This paper presents a similarity method for medical literature searches based on the biomedical literature knowledge source “MEDLINE”, the normalized MEDLINE distance, to more reasonably reflect the relevance between medical terms. This measure gives more accurate user interest descriptions through calculating the similarities of user interest terms to rerank the interest term list.The accurate user interest descriptions can be used for query refinement in keyword searches to give more personalized results for the user. This measure also improves the search results for personalization through controlling the return number of results on each topic of interest.
Keywords :
semantic similarity , query refinement , user interest , context , aware search
