Mining user intents in online interactions: Applying to discussions about medical event on SinaWeibo platform

Chenxi Cui, Wenji Mao, Xiaolong Zheng, Daniel Zeng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Mining user intents in online interactive behavior from social media data can effectively identify users’ motives behind communication and provide valuable information to aid medical decision-making and improve services. However, it is a challenging task due to the ambiguous semantic, irregular expressions and obscure intention classification categories. In this paper, we first define user intent categories based on speech act theory. On the basis of this, we develop a novel method to further classify users’ utterances according to their pragmatic functions. First, we design topic independent features by regularizing the utterance and categorizing the textual features. Then, we build a hierarchical model based on Hidden Markov Model (HMM) [1] to mine user intents in context sequence at both sentence and microblog level. Finally, we construct a dataset of microblogs about hot topics related to the medical event by a semi-automatic method. Experimental study shows the effectiveness of our method.

Original languageEnglish (US)
Title of host publicationSmart Health - International Conference, ICSH 2017, Proceedings
EditorsElena Karahanna, Indranil Bardhan, Hsinchun Chen, Daniel Dajun Zeng
PublisherSpringer-Verlag
Pages177-183
Number of pages7
ISBN (Print)9783319679631
DOIs
StatePublished - 2017
EventInternational Conference on Smart Health, ICSH 2017 - Hong Kong, Hong Kong
Duration: Jun 26 2017Jun 27 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10347 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherInternational Conference on Smart Health, ICSH 2017
CountryHong Kong
CityHong Kong
Period6/26/176/27/17

Keywords

  • Markov multinomial model
  • Medical event
  • Online communication
  • Speech act theory
  • User intention recognition

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Cui, C., Mao, W., Zheng, X., & Zeng, D. (2017). Mining user intents in online interactions: Applying to discussions about medical event on SinaWeibo platform. In E. Karahanna, I. Bardhan, H. Chen, & D. D. Zeng (Eds.), Smart Health - International Conference, ICSH 2017, Proceedings (pp. 177-183). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10347 LNCS). Springer-Verlag. https://doi.org/10.1007/978-3-319-67964-8_17