Abstract
Question answering (Q&A) communities have gained momentum recently as an effective means of knowledge sharing over the crowds, where many users are experts in the real-world and can make quality contributions in certain domains or technologies. Although the massive user-generated Q&A data present a valuable source of human knowledge, a related challenging issue is how to find those expert users effectively. In this paper, we propose a framework for finding such experts in a collaborative network. Accredited with recent works on distributed word representations, we are able to summarize text chunks from the semantics perspective and infer knowledge domains by clustering pre-trained word vectors. In particular, we exploit a graph-based clustering method for knowledge domain extraction and discern the shared latent factors using matrix factorization techniques. The proposed clustering method features requiring no post-processing of clustering indicators and the matrix factorization method is combined with the semantic similarity of the historical answers to conduct expertise ranking of users given a query. We use Stack Overflow, a website with a large group of users and a large number of posts on topics related to computer programming, to evaluate the proposed approach and conduct extensively experiments to show the effectiveness of our approach.
Original language | English |
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Title of host publication | 2017 IEEE 24th International Conference on Web Services (ICWS) : proceedings |
Editors | Ilkay Altintas, Shiping Chen |
Place of Publication | Piscataway, NJ |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Pages | 317-324 |
Number of pages | 8 |
ISBN (Electronic) | 9781538607527 |
DOIs | |
Publication status | Published - 7 Sept 2017 |
Event | 24th IEEE International Conference on Web Services, ICWS 2017 - Honolulu, United States Duration: 25 Jun 2017 → 30 Jun 2017 |
Conference
Conference | 24th IEEE International Conference on Web Services, ICWS 2017 |
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Country/Territory | United States |
City | Honolulu |
Period | 25/06/17 → 30/06/17 |
Keywords
- Expert as a Service
- Expertise finding
- Knowledge discovery
- Question answering
- Stack Overflow