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DOI: 10.14569/IJARAI.2013.020304
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Predicting Quality of Answer in Collaborative Q/A Community

Author 1: Kohei Arai
Author 2: ANIK Nur Handayani

International Journal of Advanced Research in Artificial Intelligence(IJARAI), Volume 2 Issue 3, 2013.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: Community Question Answering (CQA) services have emerged allowing information seekers pose their information need which is questions and receive answers from their fellow users, also participate in evaluating the questions or answers in a variety of topics. Within this community information seekers could interact and get information from a wide range of users, forming a heterogeneous social networks and interaction between users. A question may receive multiple answers from multiple users and the asker or the fellow users could choose the best answer. Freedom and convenience in participation, led to the diversity of the information. In this paper we present a general model to predict quality of information in a CQA by using non textual features. We showing and testing our quality measurement to a collection of question and answer pairs. In the future our models and predictions could be useful for predictor quality information as a recommender system to complete a collaborative learning.

Keywords: component; Collaborative; diversity of information; questions; answers; predict; non-textual feature

Kohei Arai and ANIK Nur Handayani, “Predicting Quality of Answer in Collaborative Q/A Community” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 2(3), 2013. http://dx.doi.org/10.14569/IJARAI.2013.020304

@article{Arai2013,
title = {Predicting Quality of Answer in Collaborative Q/A Community},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2013.020304},
url = {http://dx.doi.org/10.14569/IJARAI.2013.020304},
year = {2013},
publisher = {The Science and Information Organization},
volume = {2},
number = {3},
author = {Kohei Arai and ANIK Nur Handayani}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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