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Matching Question and Answer Using Similarity: An Experiment with Stack Overflow

Authors :
Prissadang Suta
Chun Che Fung
Jonathan H. Chan
Pornchai Mongkolnam
Source :
2018 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE).
Publication Year :
2018
Publisher :
IEEE, 2018.

Abstract

Community question and answer (CQA) sites mostly involve knowledge-bases feeding into their automated question answering systems. This paper focuses on Stack Overflow which is an online community for developers to share knowledge in computer programming. The proposed framework consists of composing of a paired Q&A corpus, followed by building of a document model with the use of paragraph vector in distributed representation via the doc2vec method, then similarity ranking to fetch a matched answer to a given question. The model pairs the two so as to represent the semantic relevance between the questions and answers generated by the proposed method. The initial experimental results have shown the system is able to provide answers automatically and with a performance of 50% accuracy when compared to expert opinions.

Details

Database :
OpenAIRE
Journal :
2018 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE)
Accession number :
edsair.doi...........e42f98e3243acc2b050426727d036bbe
Full Text :
https://doi.org/10.1109/wiecon-ece.2018.8783021