Abstract
Expert finding plays an important role in community question answering websites. Previously, most works focused on assessing the user expertise scores mainly from their past question-answering semantic features. In this work, we propose a gating mechanism to dynamically combine structural and textual representations based on past question-answering behaviors. We also use some user activities including temporal behaviors as the features, which determine the gate values. We evaluate the performance of our method on the well-known question answering sites Stackexchange and Quora. Experiments show that our approach can improve the performance on expert finding tasks.
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Acknowledgements
This work is supported by NSFC under Grant No.61532001, and MOE-ChinaMobile under Grant No.MCM20170503.
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Liu, Z., Zhang, Y. (2018). Structures or Texts? A Dynamic Gating Method for Expert Finding in CQA Services. In: Pei, J., Manolopoulos, Y., Sadiq, S., Li, J. (eds) Database Systems for Advanced Applications. DASFAA 2018. Lecture Notes in Computer Science(), vol 10828. Springer, Cham. https://doi.org/10.1007/978-3-319-91458-9_12
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DOI: https://doi.org/10.1007/978-3-319-91458-9_12
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