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New Technology of Library and Information Service  2014, Vol. 30 Issue (7): 48-55    DOI: 10.11925/infotech.1003-3513.2014.07.07
Current Issue | Archive | Adv Search |
Re-rank Retrieval Results Through Subject Indexing
Mao Jin1, Li Gang1, Cao Yujie2
1. Center for the Studies of Information Resources, Wuhan University, Wuhan 430072, China;
2. Net EaseHangzhou Inc., Hangzhou 310052, China
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[Objective] This paper tries to re-rank search results with the help of subject indexing in the process of pseudo feedback.[Methods] User queries are represented with probability distributions over subject terms by mining the user query and subject term association in the manner of language modeling. The weights of subject terms in documents are calculated by incorporating the generative language models for subject terms. Then re-calculate the score of search documents in the first retrieval and re-rank the documents according to their scores.[Results] The proposed method constructs the generative langauge models for subject terms and mines weights of subject terms in documents appropriately. The re-rank results are pervasively improved over the initial retieval.[Limitations] Different methods of mining the associations between subject terms and documents are not compared. This approach doesn't test the data sets with different scales or in different languages.[Conclusions] The re-rank approach can improve the retrieval precision,which exploits the associations between user queries, documents and subject terms.

Key wordsLanguage model      Information retrieval      Subject heading      Subject indexing      Re-rank results     
Received: 09 April 2014      Published: 20 October 2014
:  TP391.3  

Cite this article:

Mao Jin, Li Gang, Cao Yujie. Re-rank Retrieval Results Through Subject Indexing. New Technology of Library and Information Service, 2014, 30(7): 48-55.

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