Sciweavers

Share
ICDM
2006
IEEE

Applying Data Mining to Pseudo-Relevance Feedback for High Performance Text Retrieval

8 years 9 months ago
Applying Data Mining to Pseudo-Relevance Feedback for High Performance Text Retrieval
In this paper, we investigate the use of data mining, in particular the text classification and co-training techniques, to identify more relevant passages based on a small set of labeled passages obtained from the blind feedback of a retrieval system. The data mining results are used to expand query terms and to re-estimate some of the parameters used in a probabilistic weighting function. We evaluate the data mining based feedback method on the TREC HARD data set. The results show that data mining can be successfully applied to improve the text retrieval performance. We report our experimental findings in detail.
Xiangji Huang, Yan Rui Huang, Miao Wen, Aijun An,
Added 11 Jun 2010
Updated 11 Jun 2010
Type Conference
Year 2006
Where ICDM
Authors Xiangji Huang, Yan Rui Huang, Miao Wen, Aijun An, Yang Liu, Josiah Poon
Comments (0)
books