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International Conference of Reliable Information and Communication Technology

IRICT 2018: Recent Trends in Data Science and Soft Computing pp 47–56Cite as

Quality Features for Summarizing Text Forum Threads by Selecting Quality Replies

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 843))

Abstract

Text Forum Threads contain a huge volume of user-generated content derived from the discussion and information exchange among users who have similar interests. Often, some of the replies in a thread are completely off-topic which changes the discussion’s direction. This phenomenon impacts negatively on the user’s desire to continue with the discussion hence, a user might be interested in reading a few selected replies that provide a brief summary of the discussion topic. This paper aims at selecting quality replies about a topic raised in the initial-post which provide a short summary. We present a detailed analysis of the text forum threads structure based on a set of quality features for the forum summarization. Moreover, crowdsourcing platforms were used for judging the quality of the replies. Therefore, we have performed a text forum threads summarization based on replies weights and human judgment. TripAdvisor dataset has been used, therefore, the system summary helps the traveler in planning a journey. The experimental results conducted showed that the proposed approach can improve the performance of the text forum threads summarization based on forum quality features and crowdsourcing.

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Notes

  1. 1.

    https://www.tripadvisor.com.my/ShowForum-g28953-i4-New_York.html.

  2. 2.

    www.crowdflower.com/.

  3. 3.

    https://www.tripadvisor.com.my/ShowTopic-g60763-i5-k3128263-How_to_get_from_JFK_to_New_Rochelle-New_York_City_New_York.html.

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Acknowledgment

This work is supported by the Ministry of Higher Education (MOHE) and the Research Management Centre (RMC) at the Universiti Teknologi Malaysia (UTM) under the Research University Grant Category (VOT Q.J130000.2528.16H74).

Author information

Authors and Affiliations

  1. Faculty of Computing, Universiti Teknologi Malaysia, 81310, Johor Bahru, Johor, Malaysia

    Akram Osman & Naomie Salim

  2. College of Computer Science and Engineering, University of Taibah, Medina, Saudi Arabia

    Faisal Saeed

  3. Faculty of Computer Studies, International University of Africa, Khartoum, Sudan

    Ibrahim Abdelhamid

Authors
  1. Akram Osman
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  2. Naomie Salim
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  3. Faisal Saeed
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  4. Ibrahim Abdelhamid
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Corresponding author

Correspondence to Akram Osman .

Editor information

Editors and Affiliations

  1. College of Computer Science and Engineering, Taibah University, Medina, Saudi Arabia

    Faisal Saeed

  2. Information Systems Department, Faculty of Computing, Universiti Teknologi Malaysia, Skudai, Malaysia

    Nadhmi Gazem

  3. Information Technology Department, Faculty of Engineering and Information Technology, Taiz University, Taiz, Yemen

    Fathey Mohammed

  4. Information Systems Department, Faculty of Computing, Universiti Teknologi Malaysia, Skudai, Malaysia

    Abdelsalam Busalim

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Osman, A., Salim, N., Saeed, F., Abdelhamid, I. (2019). Quality Features for Summarizing Text Forum Threads by Selecting Quality Replies. In: Saeed, F., Gazem, N., Mohammed, F., Busalim, A. (eds) Recent Trends in Data Science and Soft Computing. IRICT 2018. Advances in Intelligent Systems and Computing, vol 843. Springer, Cham. https://doi.org/10.1007/978-3-319-99007-1_5

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