By Yuming Li, Guoxiong Xiang, Hongfei Lin, Mingwen Wang
ISBN-10: 981102992X
ISBN-13: 9789811029929
ISBN-10: 9811029938
ISBN-13: 9789811029936
This publication constitutes the completely refereed court cases of the fifth nationwide convention of Social Media Processing, SMP 2016, held in Nanchang, China, in October 2016.
The 24 revised complete papers provided have been rigorously reviewed and chosen from 109 submissions. The papers deal with concerns similar to: mining social media and purposes; traditional language processing; information mining; info retrieval; emergent social media processing problems.
Read or Download Social Media Processing: 5th National Conference, SMP 2016, Nanchang, China, October 29–30, 2016, Proceedings PDF
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Extra resources for Social Media Processing: 5th National Conference, SMP 2016, Nanchang, China, October 29–30, 2016, Proceedings
Sample text
Artif. Intell. Tools 17(01), 5–18 (2008) 8. : Finding experts in community-based question-answering services. In: Proceedings of the 14th ACM International Conference on Information and Knowledge Management, pp. 315–316. ACM (2005) 9. : Probabilistic question recommendation for question answering communities. In: Proceedings of the 18th International Conference on World Wide Web, pp. 1229–1230. ACM (2009) 10. : Finding expert users in community question answering. In: Proceedings of the 21st International Conference on World Wide Web, pp.
Finding experts in community-based question-answering services. In: Proceedings of the 14th ACM International Conference on Information and Knowledge Management, pp. 315–316. ACM (2005) 9. : Probabilistic question recommendation for question answering communities. In: Proceedings of the 18th International Conference on World Wide Web, pp. 1229–1230. ACM (2009) 10. : Finding expert users in community question answering. In: Proceedings of the 21st International Conference on World Wide Web, pp.
6 (2016) Predicting Best Answerers for New Questions: An Approach Leveraging Convolution Neural Networks in Community Question Answering Jian Wang ✉ , Jiqing Sun, Hongfei Lin, Hualei Dong, and Shaowu Zhang ( ) Dalian University of Technology, No. cn Abstract. Community Question Answering (CQA) websites are becoming increasingly important sources of information where users can share knowledge on various topics. These websites provide many opportunities for users to seek for help and provide answers, but they also bring new challenges.
Social Media Processing: 5th National Conference, SMP 2016, Nanchang, China, October 29–30, 2016, Proceedings by Yuming Li, Guoxiong Xiang, Hongfei Lin, Mingwen Wang
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