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Question microblog identification and answer recommendation

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Abstract

Consulting through message-updating in social network is regarded as a popular way of information seeking. However, most questions cannot receive answers or suggestions timely, and some questions even fail to get replies. Thus, identifying microblogs that contain questions (we call them “question microblog”) and recommending answers automatically are meaningful. We divide this problem into two submodules: question identification and answer recommendation. To the best of our knowledge, few attempts have been made to identify questions in microblogs due to standard features such as 5W1H (How, What, Where, When, Who, Why) are likely to be absent. The following challenging problem is how to provide users a relevant, credible, diversified and personalized answer after a microblog is recognized as a question. In this paper, we investigate the feasibility of integrating standard features and contextual features extracted from auxiliary resources and recommend a reasonable answer using collaborative filtering. Empirical results on Sina Microblog dataset demonstrate the efficacy and effectiveness of our method.

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Notes

  1. http://zhidao.baidu.com/.

  2. http://baike.baidu.com/.

  3. http://www-03.ibm.com/innovation/us/watson/.

  4. http://www.zhihu.com/.

References

  1. Adamic, L.A., Zhang, J., Bakshy, E., Ackerman, M.S.: Knowledge sharing and yahoo answers: everyone knows something. In: Proceedings of the 17th international conference on World Wide Web, pp. 665–674. ACM (2008)

  2. Akbani, R., Kwek, S., Japkowicz, N.: Applying support vector machines to imbalanced datasets. In: Machine Learning: ECML 2004, pp. 39–50. Springer, Berlin (2004)

  3. Chang, C.-C., Lin, C.-J.: Libsvm: a library for support vector machines. ACM Trans. Intell. Systems Technol. (TIST) 2(3), 27 (2011)

    Google Scholar 

  4. Chawla, N.V., Bowyer, K.W., Hall, L.O., Kegelmeyer, W.P.: Smote: synthetic minority over-sampling technique. arXiv preprint arXiv:1106.1813 (2011)

  5. Chen, K., Chen, T., Zheng, G., Jin, O., Yao, E., Yu, Y.: Collaborative personalized tweet recommendation. In: Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval, pp. 661–670. ACM (2012)

  6. Cong, G., Wang, L., Lin, C.-Y., Song, Y.-I., Sun, Y.: Finding question-answer pairs from online forums. In: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, pp. 467–474. ACM (2008)

  7. Efron, M., Winget, M.: Questions are content: a taxonomy of questions in a microblogging environment. Proc. Am. Soc. Inf. Sci. Technol. 47(1), 1–10 (2010)

    Article  Google Scholar 

  8. Erkan, G., Radev, D.R.: Lexrank: Graph-based lexical centrality as salience in text summarization. J. Artif. Intell. Res. (JAIR) 22(1), 457–479 (2004)

    Google Scholar 

  9. Gao, Y., Tang, J., Hong, R., Dai, Q., Chua, T.-S., Jain, R.: W2go: a travel guidance system by automatic landmark ranking. In: Proceedings of the international conference on Multimedia, pp. 123–132. ACM (2010)

  10. Gao, Y., Wang, F., Luan, H., Chua, T.-S.: Brand data gathering from live social media streams. In: Proceedings of International Conference on Multimedia Retrieval, pp. 169. ACM (2014)

  11. Gao, Y., Wang, M., Zha, Z.-J., Shen, J., Li, X.: Visual-textual joint relevance learning for tag-based social image search. IEEE Trans. Image Process. 22(1), 363–376 (2013)

    Article  MathSciNet  Google Scholar 

  12. Gupta, V., Lehal, G.S.: A survey of text summarization extractive techniques. J. Emerg. Technol. Web Intell, 2(3) (2010)

  13. Han, J., Pei, J., Mortazavi-Asl, B., Pinto, H., Chen, Q., Dayal, U., Hsu, M.C.: Prefixspan: Mining sequential patterns efficiently by prefix-projected pattern growth. In: Proceedings of the 17th International Conference on Data Engineering, pp. 215–224 (2001)

  14. Hong, L., Davison, B.D.: A classification-based approach to question answering in discussion boards. In: Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval, pp. 171–178. ACM (2009)

  15. Horowitz, D., Kamvar, S.D.: The anatomy of a large-scale social search engine. In: Proceedings of the 19th international conference on World wide web, pp. 431–440. ACM (2010)

  16. Jeon, J., Croft, W.B., Lee, J.H.: Finding similar questions in large question and answer archives. In: Proceedings of the 14th ACM international conference on Information and knowledge management, pp. 84–90. ACM (2005)

  17. Li, B., Si, X., Lyu, M.R., King, I., Chang, E.Y.: Question identification on twitter. In: Proceedings of the 20th ACM international conference on Information and knowledge management, pp. 2477–2480. ACM (2011)

  18. Li, J., Li, L., Li, T.: Mssf: a multi-document summarization framework based on submodularity. In: Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval, pp. 1247–1248. ACM (2011)

  19. Lin, C.-Y.: Rouge: A package for automatic evaluation of summaries. In: Text Summarization Branches Out: Proceedings of the ACL-04 Workshop, pp. 74–81 (2004)

  20. Liu, Q., Agichtein, E., Dror, G., Gabrilovich, E., Maarek, Y., Pelleg, D., Szpektor, I.: Predicting web searcher satisfaction with existing community-based answers. In: Proceedings of SIGIR, pp. 415–424 (2011)

  21. Morris, M.R., Teevan, J., Panovich, K.: A comparison of information seeking using search engines and social networks. In: Proceedings of the Fourth International AAAI Conference on Weblogs and Social Media (2010)

  22. Nichols, J., Kang, J.-H.: Asking questions of targeted strangers on social networks. In: Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work, pp. 999–1002. ACM (2012)

  23. Ounis, I., Amati, G., Plachouras, V., He, B., Macdonald, C., Lioma, C.: Terrier: a high performance and scalable information retrieval platform. In: Proceedings of ACM SIGIR’06 Workshop on Open Source Information Retrieval (OSIR 2006) (2006)

  24. Panovich, K., Miller, R., Karger, D.: Tie strength in question and answer on social network sites. In: Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work, pp. 1057–1066. ACM (2012)

  25. Paul, S.A., Hong, L., Chi, E.H.: Is twitter a good place for asking questions? a characterization study. Proceedings of ICWSM 2011, pp. 1–4 (2011)

  26. Paul, S.A., Hong, L., Chi, E.H.: Who is authoritative? understanding reputation mechanisms in quora. arXiv preprint arXiv:1204.3724 (2012)

  27. Qiu, X., Zhang, Q., Huang, X.: Fudannlp: A toolkit for chinese natural language processing. In: Proceedings of Annual Meeting of the Association for Computational Linguistics (2013)

  28. Quarteroni, S., Manandhar, S.: User modelling for personalized question answering. In: AI* IA 2007: Artificial Intelligence and Human-Oriented Computing, pp. 386–397. Springer, Berlin (2007)

  29. Spitkovsky, V.I., Alshawi, H., Chang, A.X., Jurafsky, D.: Unsupervised dependency parsing without gold part-of-speech tags. In: Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing (EMNLP 2011) (2011)

  30. Xiaoyuan, S., Khoshgoftaar, T.M.: A survey of collaborative filtering techniques. Adv. Artif. Intell. 2009, 4 (2009)

    Google Scholar 

  31. Teevan, J., Ramage, D., Morris, M.R.: # twittersearch: a comparison of microblog search and web search. In: Proceedings of the fourth ACM international conference on Web search and data mining, pp. 35–44. ACM (2011)

  32. Tomasoni, M., Huang, M.: Metadata-aware measures for answer summarization in community question answering. In: Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, pp. 760–769. Association for Computational Linguistics (2010)

  33. Wang, B., Liu, B., Sun, C., Wang, X., Sun, L.: Extracting chinese question-answer pairs from online forums. In: IEEE International Conference on Systems, man and cybernetics, 2009. SMC 2009, pp. 1159–1164. IEEE (2009)

  34. Wang, K., Chua, T.-S.: Exploiting salient patterns for question detection and question retrieval in community-based question answering. In: Proceedings of the 23rd International Conference on Computational Linguistics, pp. 1155–1163. Association for Computational Linguistics (2010)

  35. Xue, X., Jeon, J., Croft, W.B.: Retrieval models for question and answer archives. In: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, pp. 475–482. ACM (2008)

  36. Yih, W., Goodman, J., Vanderwende, L., Suzuki, H.: Multi-document summarization by maximizing informative content-words. In: IJCAI, volume 2007, p. 20 (2007)

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Acknowledgments

Xiangrong Liu is partially supported by National Natural Science Foundation of China (Grant Nos. 61373076, 60971085), the Fundamental Research Funds for the Central Universities (No. 2013121026), Natural Science Foundation of Fujian Province of China 2010J01350, Base Research Project of Shenzhen Bureau of Science, Technology, and Information (JC201006030858A). Chen Lin is partially supported by Shanghai Key Laboratory of Intelligent Information Processing under Grant No. IIPL-2011-004, China Natural Science Foundation under Grant Nos. NSFC61102136, NSFC61370010, NSFC81101115, the Natural Science Foundation of Fujian Province of China under Grant Nos. 2011J05158, 2011J01371, Fundamental Research Funds for Central Universities under Grant No. 2011121049, CCF-Tencent Open Research Fund under Grant No. CCF-Tencent20130101, Base Research Project of Shenzhen Bureau of Science,Technology, and Information under Grand No. JCYJ20120618155655087.

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Authors and Affiliations

  1. School of Information Science and Engineering, Xiamen University, Xiamen, China

    Xiangrong Liu, Runquan Xie, Chen Lin & Liujuan Cao

  2. Shenzhen Research Institute of Xiamen University, Shenzhen, China

    Xiangrong Liu & Chen Lin

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  1. Xiangrong Liu
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  2. Runquan Xie
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Correspondence to Liujuan Cao.

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Liu, X., Xie, R., Lin, C. et al. Question microblog identification and answer recommendation. Multimedia Systems 22, 487–496 (2016). https://doi.org/10.1007/s00530-014-0411-z

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