By Hartung, Eisert, Girod
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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.
Digital Watermarking of MPEG-4 Facial Animation Parameters by Hartung, Eisert, Girod
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