Abstract
In the expert ranking process, we put forward an expert ranking method based on list with associated features, in order to use effectively expert relationship and the relative relationship of the expert list. First, construct a correlation model of query and expert by evidence documents, expert display and implicit relationships and expert metadata. Then sort experts by the ListNet algorithm based on the list. Finally perform an experiment under the expert list, and the MAP value is 0.3506. The result shows that this method can effectively improve the accuracy of expert sorting, and expert relationship and the relative relationship of the expert list play an important role in the expert ranking.
Supported by the China National Nature Science Foundation (No. 61175068, 61472168, 61163004), and The Key Project of Yunnan Nature Science Foundation (No. 2013FA130).
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Wei, S., Yu, Z., Chen, F., Mao, C., Guo, J. (2015). The Expert Ranking Method Based on Listwise with Associated Features. In: Zhang, X., Sun, M., Wang, Z., Huang, X. (eds) Social Media Processing. SMP 2015. Communications in Computer and Information Science, vol 568. Springer, Singapore. https://doi.org/10.1007/978-981-10-0080-5_18
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DOI: https://doi.org/10.1007/978-981-10-0080-5_18
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