INSTITUTIONAL DIGITAL REPOSITORY

Browsing by Author "Verma, A. A."

Browsing by Author "Verma, A. A."

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  • Implicit visual attention feedback system for wikipedia users 
    Dubey, N.; Iyengar, S. R. S.; Verma, A. A.; Setia, S. (2021-11-15)
    The complex collaborative structure of Wikipedia has attracted researchers from various domains, such as social networks, humancomputer interaction, and collective intelligence. Yet, a few focus on the readers’ perception ...
  • KDAP: an open source toolkit to accelerate knowledge building research 
    Verma, A. A.; Setia, S.; Iyengar, S.R.S.; Dubey, N. (2021-07-03)
    With the success of crowdsourced portals, such as Wikipedia, Stack Overflow, Quora, and GitHub, a class of researchers is driven towards understanding the dynamics of knowledge building on these portals. Even though ...
  • QWiki: need for QnA & wiki to Co-exist 
    Setia, S.; Iyengar, S.R.S.; Verma, A. A. (2021-07-03)
    Access to knowledge has never been as easy and quick as it has been in the 21st century. With the advent of the Internet and crowdsourced knowledge building portals such as Wikipedia, Stack Exchange, Quora, and GitHub, ...
  • Tracing the factoids: the anatomy of information Re-organization in wikipedia articles 
    Verma, A. A.; Dubey, N.; Iyengar, S. R. S.; Setia, S. (2021-07-21)
    Wikipedia articles are known for their exhaustive knowledge and extensive collaboration. Users perform various tasks that include editing in terms of adding new facts or rectifying some mistakes, looking up new topics, ...
  • WikiGaze: Gaze-based personalized summarization of wikipedia reading session 
    Dubey, N.; Setia, S.; Verma, A. A.; Iyengar, S.R.S. (2021-07-02)
    Wikipedia is an open-content encyclopedia that receives billions of page views per month. It has been observed that in a single reading session, Wikipedia users visit multiple articles. To reduce the problems of overload ...
  • WiTPy: a toolkit to parse and analyse wikipedia talk pages 
    Verma, A. A.; Iyengar, S.R.S.; Gandhi, N. (2021-06-22)
    In this article, we propose an opensource toolkit to extract, parse, and analyze the Wikipedia talk pages. The core parser uses a tree-based approach to parse the unstructured comments and a JSON(JavaScript Object ...