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Relative difficulty estimation in community answering services

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dc.contributor.author Thukral, Deepak
dc.contributor.author Goyal, Vikram (Advisor)
dc.contributor.author Chakraborty, Tanmoy (Advisor)
dc.date.accessioned 2018-09-24T10:39:06Z
dc.date.available 2018-09-24T10:39:06Z
dc.date.issued 2018-04-18
dc.identifier.uri http://repository.iiitd.edu.in/xmlui/handle/123456789/663
dc.description.abstract Automatic estimation of relative difficulty of a pair of questions is an important and challenging problem in community question answering (CQA) services. There are limited studies which addressed this problem. Past studies mostly leveraged expertise of users answering the questions and barely considered other properties of CQA services such as metadata of users and posts,temporal information and textual content. In this paper, we propose a system, a novel system that maps this problem to a network-aided edge directionality prediction problem. Given a question on a crowd sourced platform, we gauge the difficulty of the question. We used various graph models in order to model our intuition of how difficulty is associated with questions, the answerers, the asker and how over time the difficulty of one’s questions change en_US
dc.language.iso en_US en_US
dc.publisher IIIT-Delhi en_US
dc.subject Data Analysis en_US
dc.subject Stackoverflow en_US
dc.subject Graph Mining en_US
dc.subject Time-evolving networks en_US
dc.subject Network Construction en_US
dc.subject Edge Directionality Prediction en_US
dc.title Relative difficulty estimation in community answering services en_US
dc.type Other en_US

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