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Users’ satisfaction based ranking for Yahoo Answers

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Abstract

Community based question and answer websites; such as, Yahoo Answers, Stack Overflow, Stack Exchange and Quora are briskly generating content in the form of questions and answers posted by users. These online discussion forums allow the users to append and edit the content easily. Therefore, a huge amount of content has accumulated over the time, which is beneficial for the search engine users for addressing their queries to the related content. On the other hand, the task of maintaining the answer quality and ranking of retrieved results has always been a challenging task for the websites that accumulate user’s generated data. Here, the problem of ranking the answers based on the user’s satisfaction is investigated. The best answers based on their ranking are identified. Three techniques are proposed, which are Relevance Features (REL_FS), Readability Features (RED_FS), and Weighted Answer Rank WEIGHTED ANS_RANK. REL_FS performs a summation of relevance features, RES_FS sums the readability features and WEIGHTED ANS_RANK performs a summation of REL_FS and RED_FS to deal with the task. Proposed methods compute the rank of answers according to both the relevance and readability of answers. Experimental results show proposed methods ability of providing effective ranking of answers for the selection of best answers. Moreover, it also measures the consistency of ranked answers with the help of a detailed correlational analysis.

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Data availability

The yahoo answers dataset has been obtained from Yahoo web-scope with the authorized permission of Yahoo Answer for research purposes only. Interested readers can obtain the data from Yahoo web-scope.

Notes

  1. academicrelations@yahoo-inc.com or visit http://research.yahoo.com/Academic Relations for details on obtaining Yahoo! Webscope data sets.

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Authors and Affiliations

  1. Department of Computer Science and Artificial Intelligence, College of Computer Science and Engineering, University of Jeddah, Jeddah, Saudi Arabia

    Ameen Banjar & Riad Alharbey

  2. Faculty of Computing and Information Technology, Department of Computer Science, International Islamic University, Islamabad, Pakistan

    Awais Shaheen & Tehmina Amjad

  3. Khoury College of Computer Science, Northeastern University, Silicon Valley, San Jose, CA, USA

    Tehmina Amjad

  4. Faculty of Resilience, Rabdan Academy, Abu Dhabi, United Arab Emirates

    Ali Daud

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  1. Ameen Banjar
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  2. Awais Shaheen
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  3. Tehmina Amjad
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  4. Riad Alharbey
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Correspondence to Tehmina Amjad.

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Banjar, A., Shaheen, A., Amjad, T. et al. Users’ satisfaction based ranking for Yahoo Answers. Multimed Tools Appl 83, 71265–71284 (2024). https://doi.org/10.1007/s11042-024-18433-3

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  • DOI: https://doi.org/10.1007/s11042-024-18433-3

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