TY - GEN
T1 - A topic based document relevance ranking model
AU - Gao, Yang
AU - Xu, Yue
AU - Li, Yuefeng
N1 - Publisher Copyright:
© Copyright 2014 by the International World Wide Web Conferences Steering Committee.
PY - 2014/4/7
Y1 - 2014/4/7
N2 - Topic modelling has been widely used in the fields of in- formation retrieval, text mining, machine learning, etc. In this paper, we propose a novel model, Pattern Enhanced Topic Model (PETM), which makes improvements to topic modelling by semantically representing topics with discrim- inative patterns, and also makes innovative contributions to information filtering by utilising the proposed PETM to de- Termine document relevance based on topics distribution and maximum matched patterns proposed in this paper. Exten- sive experiments are conducted to evaluate the effectiveness of PETM by using the TREC data collection Reuters Corpus Volume 1. The results show that the proposed model signifi- cantly outperforms both state-of-the-art term-based models and pattern-based models.
AB - Topic modelling has been widely used in the fields of in- formation retrieval, text mining, machine learning, etc. In this paper, we propose a novel model, Pattern Enhanced Topic Model (PETM), which makes improvements to topic modelling by semantically representing topics with discrim- inative patterns, and also makes innovative contributions to information filtering by utilising the proposed PETM to de- Termine document relevance based on topics distribution and maximum matched patterns proposed in this paper. Exten- sive experiments are conducted to evaluate the effectiveness of PETM by using the TREC data collection Reuters Corpus Volume 1. The results show that the proposed model signifi- cantly outperforms both state-of-the-art term-based models and pattern-based models.
KW - Pattern mining
KW - Relevance ranking
KW - Topic models
UR - http://www.scopus.com/inward/record.url?scp=84990955553&partnerID=8YFLogxK
U2 - 10.1145/2567948.2577289
DO - 10.1145/2567948.2577289
M3 - Conference contribution
AN - SCOPUS:84990955553
T3 - WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web
SP - 271
EP - 272
BT - WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web
PB - Association for Computing Machinery, Inc
T2 - 23rd International Conference on World Wide Web, WWW 2014
Y2 - 7 April 2014 through 11 April 2014
ER -