Expert as a service: Software expert recommendation via knowledge domain embeddings in stack overflow

Publication Type

Conference Proceeding Article

Publication Date

9-2017

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.

Keywords

Expert as a Service, Expertise finding, Knowledge discovery, Question answering, Stack Overflow, Cluster analysis, Computer programming, Data mining, Factorization, Graphic methods, Matrix algebra, Natural language processing systems, Semantics, Websites, Collaborative network, Expert as a Service, Expert recommendations, Expertise finding, Graph-based clustering, Matrix factorizations, Question Answering, Stack overflow, Web services

Discipline

Programming Languages and Compilers | Software Engineering

Publication

Proceedings of the 24th International Conference on Web Services, ICWS 2017, Honolulu, United States, June 25-30

First Page

317

Last Page

324

ISBN

9781538607527

Identifier

10.1109/ICWS.2017.122

Publisher

Institute of Electrical and Electronics Engineers Inc.

City or Country

Honolulu, United States

Additional URL

https://doi.org/10.1109/ICWS.2017.122

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