Discovering Domain Experts in Online Q&A Communities

doi:10.3969/j.issn.1006-2475.2018.09.015

Abstract

Abstract: In this paper, we propose a question-answerer-topic model according to the generation procedure of answers in online Q&A communities, to model the topic distribution of question-answerer pairs. Then we calculate the professional level of users under different topics by incorporating the voting number of each answer in each question. Finally we propose an improved topic-sensitive PageRank model based on the thinking of link analysis to calculate the final expert score of each user under specific topics. The experiments and comparative analysis based on a real data set from a Chinese online Q&A community Zhihu in the field of artificial intelligence are carried out. The experimental results show that the proposed method obviously outperforms other existing expert finding methods.

Key words: online Q&A communities, topic model, link analysis, experts finding

CLC Number:

TP391

LI Ke-lin. Discovering Domain Experts in Online Q&A Communities[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2018.09.015.

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