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Probabilistic question recommendation for question answering communities

Published: 20 April 2009 Publication History

Abstract

User-Interactive Question Answering (QA) communities such as Yahoo! Answers are growing in popularity. However, as these QA sites always have thousands of new questions posted daily, it is difficult for users to find the questions that are of interest to them. Consequently, this may delay the answering of the new questions. This gives rise to question recommendation techniques that help users locate interesting questions. In this paper, we adopt the Probabilistic Latent Semantic Analysis (PLSA) model for question recommendation and propose a novel metric to evaluate the performance of our approach. The experimental results show our recommendation approach is effective.

References

[1]
L. A. Adamic, J. Zhang, E. Bakshy, and M. S. Ackerman. Knowledge sharing and yahoo answers: everyone knows something. In WWW '08.
[2]
T. Hofmann. Probabilistic latent semantic indexing. In SIGIR '99.
[3]
A. Popescul, L. H. Ungar, D. M. Pennock, and S. Lawrence. Probabilistic models for unified collaborative and content-based recommendation in sparse-data environments. In UAI '01.

Cited By

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  • (2023)Automatic Skill-Oriented Question Generation and Recommendation for Intelligent Job InterviewsACM Transactions on Information Systems10.1145/360455242:1(1-32)Online publication date: 13-Jun-2023
  • (2023)SSC-CF: Semantic similarity and clustering-based collaborative filtering for expert recommendation in community question answering websitesInternational Journal of Information Technology10.1007/s41870-023-01458-615:8(4243-4257)Online publication date: 28-Sep-2023
  • (2023)Similar question retrieval with incorporation of multi-dimensional quality analysis for community question answeringNeural Computing and Applications10.1007/s00521-023-09266-636:7(3663-3679)Online publication date: 6-Dec-2023
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  1. Probabilistic question recommendation for question answering communities

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      cover image ACM Conferences
      WWW '09: Proceedings of the 18th international conference on World wide web
      April 2009
      1280 pages
      ISBN:9781605584874
      DOI:10.1145/1526709

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 20 April 2009

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      Author Tags

      1. PLSA
      2. question answering
      3. question recommendation

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      Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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      Cited By

      View all
      • (2023)Automatic Skill-Oriented Question Generation and Recommendation for Intelligent Job InterviewsACM Transactions on Information Systems10.1145/360455242:1(1-32)Online publication date: 13-Jun-2023
      • (2023)SSC-CF: Semantic similarity and clustering-based collaborative filtering for expert recommendation in community question answering websitesInternational Journal of Information Technology10.1007/s41870-023-01458-615:8(4243-4257)Online publication date: 28-Sep-2023
      • (2023)Similar question retrieval with incorporation of multi-dimensional quality analysis for community question answeringNeural Computing and Applications10.1007/s00521-023-09266-636:7(3663-3679)Online publication date: 6-Dec-2023
      • (2022)Natural language why-question in Business Intelligence applications: model and recommendation approachCluster Computing10.1007/s10586-022-03593-425:6(3875-3898)Online publication date: 18-May-2022
      • (2021)Learner question’s correctness assessment and a guided correction method: enhancing the user experience in an interactive online learning systemPeerJ Computer Science10.7717/peerj-cs.5327(e532)Online publication date: 25-May-2021
      • (2021)LDA-based term profiles for expert finding in a political settingJournal of Intelligent Information Systems10.1007/s10844-021-00636-xOnline publication date: 23-Mar-2021
      • (2020)Best Answerers Prediction With Topic Based GAT In Q&A SitesProceedings of the 12th Asia-Pacific Symposium on Internetware10.1145/3457913.3457935(156-164)Online publication date: 1-Nov-2020
      • (2019)Towards Decisional Natural Language Why-Question Recommendation Approach in Business Intelligence Context2019 International Conference on Networking and Advanced Systems (ICNAS)10.1109/ICNAS.2019.8807856(1-6)Online publication date: Jun-2019
      • (2019)Predicting the Timing and Quality of Responses in Online Discussion Forums2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS)10.1109/ICDCS.2019.00191(1931-1940)Online publication date: Jul-2019
      • (2019)Task recommender system using semantic clustering to identify the right personnelVINE Journal of Information and Knowledge Management Systems10.1108/VJIKMS-08-2018-0068Online publication date: 12-Mar-2019
      • Show More Cited By

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