E-WISE: An Expertise-Driven Recommendation Platform for Web Question Answering Systems

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9114)

Abstract

This demo presents E-WISE, an expertise-driven recommendation platform built upon Web Question Answering (QA) systems to assist askers in question-answering process. Despite that crowdsourcing knowledge (e.g., on-line question-answering) is becoming increasingly important, it remains a big challenge to accelerate its process. E-WISE blends the recently developed methods for knowledge crowdsourcing acceleration, including 1) an edit suggestion component to improve question quality; 2) a question routing component that suggests a list of ranked answerers. Both components are automatic, and meanwhile enable a human controlling part: askers can make their decisions in selecting the right edits/answerers among the suggested ones, which guarantees the effectiveness of the suggesting components and provides feedback to the suggesting methods. E-WISE will be demonstrated through a case study on Stack Overflow – a popular QA systems, to exemplify its functions and potential in on-line knowledge creation.

Keywords

Crowdsourcing Knowledge creation Question answering Edit suggestion Question routing 

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References

  1. 1.
    Kittur, A., Nickerson, J.V., Bernstein, M., Gerber, E., Shaw, A., Zimmerman, J., Lease, M., Horton, J.: The future of crowd work. In: CSCW 2013, pp. 1301–1318. ACM, New York (2013)Google Scholar
  2. 2.
    Ravi, S., Pang, B., Rastogi, V., Kumar, R.: Great question! question quality in community Q&A. In: ICWSM 2014, pp. 426–435. AAAI, Palo Alto (2014)Google Scholar
  3. 3.
    Yang, J., Hauff, C., Bozzon, A., Houben, G.J.: Asking the right question in collaborative Q&A systems. In: Hypertext 2014, pp. 179–189. ACM, New York (2014)Google Scholar
  4. 4.
    Yang, J., Tao, K., Bozzon, A., Houben, G.-J.: Sparrows and owls: characterisation of expert behaviour in stackoverflow. In: Dimitrova, V., Kuflik, T., Chin, D., Ricci, F., Dolog, P., Houben, G.-J. (eds.) UMAP 2014. LNCS, vol. 8538, pp. 266–277. Springer, Heidelberg (2014) Google Scholar
  5. 5.
    Hendler, J., Berners-Lee, T.: From the Semantic Web to Social Machines: a Research Challenge for AI on the World Wide Web. Artificial Intelligence 174(2), 156–161 (2010)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Delft University of TechnologyDelftThe Netherlands

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