THUIR at TREC2008: Relevance Feedback Track
Abstract
Our group has participated into Relevance Feedback (RF) Track in TREC2008. In our experiments, two kinds of techniques, query expansion and search result re-ranking based on document relevance model, are adopted to improve the retrieval performance. The TMiner search engine, from IR group of Tsinghua University, is used as our text retrieval system. Tsinghua University Information Retrieval Group (THUIR) has participated into the first Relevance Feedback Track of TREC2008. The TMiner search engine has been used as our text retrieval system, because the processing capability and flexibility of this system on large text data has been testified during many years' Web Track and Terabyte Track. In the track, we studied two approaches: 1) query expansion, 2) search result re-ranking based on document relevance model. Terms in the annotated documents (feedback) are used to expand the original query; the new born queries are sent to the search engine for further information retrieval; users get the documents retrieved by the expanded queries.
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 01, 2008
- Accession Number
- ADA512686
Entities
People
- Bo Zhou
- Min Zhang
- Qi Fang
- Rongwei Cen
- Shaoping Ma
- Yiqun Liu
Organizations
- Tsinghua University