›› 2015,Vol. 30 ›› Issue (5): 1054-1062.doi: 10.1007/s11390-015-1581-7

所属专题： Artificial Intelligence and Pattern Recognition； Data Management and Data Mining

• Special Section on Selected Paper from NPC 2011 • 上一篇    下一篇

基于在线问答社区的意图相关产品挖掘

Jun-Wen Duan(段俊文), Yi-Heng Chen(陈毅恒), Member, CCF Ting Liu*(刘挺), Senior Member, CCF, ACM, Xiao Ding(丁效), Member, CCF   

  1. School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
  • 收稿日期:2014-11-17 修回日期:2015-07-09 出版日期:2015-09-05 发布日期:2015-09-05
  • 通讯作者: Ting Liu E-mail:tliu@ir.hit.edu.cn
  • 作者简介:Jun-Wen Duan received his B.E. degree in computer science and technology from Harbin Institute of Technology, Harbin, in 2013. Currently, he is a Ph.D. candidate in Harbin Institute of Technology. His current research interests include natural language processing, social computing, and text mining.
  • 基金资助:

    The research is supported by the National Basic Research 973 Program of China under Grant No. 2014CB340503 and the National Natural Science Foundation of China under Grant Nos. 61133012, 61202277, and 61472107.

Mining Intention-Related Products on Online Q&A Community

Jun-Wen Duan(段俊文), Yi-Heng Chen(陈毅恒), Member, CCF Ting Liu*(刘挺), Senior Member, CCF, ACM, Xiao Ding(丁效), Member, CCF   

  1. School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
  • Received:2014-11-17 Revised:2015-07-09 Online:2015-09-05 Published:2015-09-05
  • Contact: Ting Liu E-mail:tliu@ir.hit.edu.cn
  • About author:Jun-Wen Duan received his B.E. degree in computer science and technology from Harbin Institute of Technology, Harbin, in 2013. Currently, he is a Ph.D. candidate in Harbin Institute of Technology. His current research interests include natural language processing, social computing, and text mining.
  • Supported by:

    The research is supported by the National Basic Research 973 Program of China under Grant No. 2014CB340503 and the National Natural Science Foundation of China under Grant Nos. 61133012, 61202277, and 61472107.

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在线社交媒体上的用户生成内容吸引了来自服务/产品提供商的注意, 因为其中包含大量潜在的商业机会。然而, 之前的工作主要集中在用户消费意图的识别, 挖掘意图相关产品很少有工作涉及。本文中, 我们提出了一种新的基于在线问答社区的意图相关产品的挖掘方法。将问答对作为数据源, 我们首先基于依存分析自动地抽取其中的候选产品。之后, 通过搭配抽取的模型, 我们从候选产品集合中识别出真正的意图相关产品。

Abstract: User generated content on social media has attracted much attention from service/product providers, as it contains plenty of potential commercial opportunities. However, previous work mainly focuses on user consumption intention (CI) identification, and little effort has been spent to mine intention-related products. In this paper, focusing on the Baby & Child Care domain, we propose a novel approach to mine intention-related products on online question and answer (Q&A) community. Making use of the question-answering pairs as data source, we first automatically extract candidate products based on dependency parser. And then by means of the collocation extraction model, we identify the real intention-related products from the candidate set. The experimental results on our carefully constructed evaluation dataset show that our approach achieves better performance than two natural baseline methods.

[1] Ashkan A, Clarke C L. Term-based commercial intent analysis. In Proc. the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval, July 2009, pp.800-801.

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[3] Ding X, Liu T, Duan J, Nie J Y. Mining user consumption intention from social media using domain adaptive convolutional neural network. In Proc. the 29th AAAI Conference on Artificial Intelligence, January 2015, pp.2395-2389.

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[12] Zhao W X, Jiang J, He J, Song Y, Achananuparp P, Lim E P, Li X. Topical keyphrase extraction from Twitter. In Proc. the 49th Annual Meeting of the Association for Computational Linguistics:Human Language Technologies, Volume 1, June 2011, pp.379-388.

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