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| A Semantic Similarity Weighted Query Term Proximity Framework for Information Retrieval |
| QIAO Ya-Nan1,2,LIU Yue-Hu1,QI Yong1 |
1. School of Electronic and Information Engineering,Xian Jiaotong University,Xian 710049
2. State Key Laboratory for Novel Software Technology,Nanjing University,Nanjing 210093 |
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Abstract Traditional proximity retrieval models treat query terms equally and they do not distinguish the proximities between query terms. Thus,the parallel concept effect is caused,and the performance of many query term proximity based information retrieval models is affected. A semantic similarity weighted query term proximity framework is proposed.The statistics of query term proximity are weighted in this framework by the semantic similarities between query terms,and then the in-depth information needs can be concluded and mined.Experimental results show that compared with traditional proximity retrieval models,the proposed framework greatly improves the performance of traditional proximity retrieval models and avoids the parallel concept effect efficiently for short queries.
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Received: 12 June 2012
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2013, Vol. 26 
