Relevance Feedback based on Constrained Clustering: FDU at TREC 09
Abstract
We introduce our participation of the TREC Relevance Feedback(RF) TRACK in 2009. The RF09 TRACK is focused on the explicit relevant feedback, where a few relevant and irrelevant documents are available to each query. Our system is implemented under the framework of probabilistic language model. We apply the constrained clustering on the top returned documents and extract the expanded words to reform the query. We also extract the named entities from the explicit relevant documents to expand the query. The experiment was conducted on the ClueWeb09 TREC Category B, which is a new and huge test collection for the TREC TRACKs. The evaluation result shows the performance of the constrained clustering.
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 01, 2009
- Accession Number
- ADA517715
Entities
People
- Bingqing Wang
- Xuanjing Huang
Organizations
- Fudan University