Mining Community-Based Top-k Experts and Learners in Online Question Answering Systems

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 379)

Abstract

Online Question Answering Systems are very popular and helpful for programming community. In these systems, users can post questions, answer the questions, collaboratively tag the questions, and vote for quality answers. This paper implements a link structure-based Top-k Experts and Learners finding algorithm using Stanford Network Analysis Project (SNAP) Library. Experiments are done on real data taken from Stack Overflow that mainly focuses on computer programming and the results show that link analysis techniques are more suitable for analyzing online question answering systems.

Keywords

Graph mining Social network analysis Expert finding Recommendation system Community-based question answering system 

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Copyright information

© Springer India 2016

Authors and Affiliations

  • S Rao Chintalapudi
    • 1
  • M. H. M. Krishna Prasad
    • 1
  1. 1.Department of CSEUniversity College of Engineering Kakinada (A), JNTUKKakinadaIndia

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