TY - GEN
T1 - Structural topic model for latent topical structure analysis
AU - Wang, Hongning
AU - Zhang, Duo
AU - Zhai, Cheng Xiang
PY - 2011
Y1 - 2011
N2 - Topic models have been successfully applied to many document analysis tasks to discover topics embedded in text. However, existing topic models generally cannot capture the latent topical structures in documents. Since languages are intrinsically cohesive and coherent, modeling and discovering latent topical transition structures within documents would be beneficial for many text analysis tasks. In this work, we propose a new topic model, Structural Topic Model, which simultaneously discovers topics and reveals the latent topical structures in text through explicitly modeling topical transitions with a latent first-order Markov chain. Experiment results show that the proposed Structural Topic Model can effectively discover topical structures in text, and the identified structures significantly improve the performance of tasks such as sentence annotation and sentence ordering.
AB - Topic models have been successfully applied to many document analysis tasks to discover topics embedded in text. However, existing topic models generally cannot capture the latent topical structures in documents. Since languages are intrinsically cohesive and coherent, modeling and discovering latent topical transition structures within documents would be beneficial for many text analysis tasks. In this work, we propose a new topic model, Structural Topic Model, which simultaneously discovers topics and reveals the latent topical structures in text through explicitly modeling topical transitions with a latent first-order Markov chain. Experiment results show that the proposed Structural Topic Model can effectively discover topical structures in text, and the identified structures significantly improve the performance of tasks such as sentence annotation and sentence ordering.
UR - http://www.scopus.com/inward/record.url?scp=84859034862&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84859034862&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84859034862
SN - 9781932432879
T3 - ACL-HLT 2011 - Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies
SP - 1526
EP - 1535
BT - ACL-HLT 2011 - Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics
T2 - 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL-HLT 2011
Y2 - 19 June 2011 through 24 June 2011
ER -