TY - GEN
T1 - A study of document weight smoothness in pseudo relevance feedback
AU - Zhang, Peng
AU - Song, Dawei
AU - Zhao, Xiaochao
AU - Hou, Yuexian
PY - 2010
Y1 - 2010
N2 - In pseudo relevance feedback (PRF), the document weight which indicates how important a document is for the PRF model, plays a key role. In this paper, we investigate the smoothness issue of the document weights in PRF. The term smoothness means that the document weights decrease smoothly (i.e. gradually) along the document ranking list, and the weights are smooth (i.e. similar) within topically similar documents. We postulate that a reasonably smooth document-weighting function can benefit the PRF performance. This hypothesis is tested under a typical PRF model, namely the Relevance Model (RM). We propose a two-step document weight smoothing method, the different instantiations of which have different effects on weight smoothing. Experiments on three TREC collections show that the instantiated methods with better smoothing effects generally lead to better PRF performance. In addition, the proposed method can significantly improve the RM's performance and outperform various alternative methods which can also be used to smooth the document weights.
AB - In pseudo relevance feedback (PRF), the document weight which indicates how important a document is for the PRF model, plays a key role. In this paper, we investigate the smoothness issue of the document weights in PRF. The term smoothness means that the document weights decrease smoothly (i.e. gradually) along the document ranking list, and the weights are smooth (i.e. similar) within topically similar documents. We postulate that a reasonably smooth document-weighting function can benefit the PRF performance. This hypothesis is tested under a typical PRF model, namely the Relevance Model (RM). We propose a two-step document weight smoothing method, the different instantiations of which have different effects on weight smoothing. Experiments on three TREC collections show that the instantiated methods with better smoothing effects generally lead to better PRF performance. In addition, the proposed method can significantly improve the RM's performance and outperform various alternative methods which can also be used to smooth the document weights.
KW - Document weight smoothness
KW - Pseudo relevance feedback
KW - Query language model
KW - Relevance Model
UR - http://www.scopus.com/inward/record.url?scp=78650906319&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-17187-1_50
DO - 10.1007/978-3-642-17187-1_50
M3 - Conference contribution
AN - SCOPUS:78650906319
SN - 3642171869
SN - 9783642171864
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 527
EP - 538
BT - Information Retrieval Technology - 6th Asia Information Retrieval Societies Conference, AIRS 2010, Proceedings
T2 - 6th Asia Information Retrieval Societies Conference, AIRS 2010
Y2 - 1 December 2010 through 3 December 2010
ER -