Abstract
The rapidly increasing popularity of social computing has encouraged Internet users to interact with online discussion forums to discuss various topics. Online discussion forums have been used as a medium for collaborative learning that supports knowledge sharing and information exchanging between users. One of the serious problems of such environments is high volume of shared data that causes a difficulty for users to locate relevant content to their preferences. In this paper, we propose an architecture of a forum recommender system that recommends relevant post messages to users based on content-based filtering and latent semantic analysis which in turn will increase the dynamism of online forums, help users to discover relevant post messages, and prevent them from redundant post messages as well as bad content post messages.
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Albatayneh, N.A., Ghauth, K.I., Chua, FF. (2014). A Semantic Content-Based Forum Recommender System Architecture Based on Content-Based Filtering and Latent Semantic Analysis. In: Herawan, T., Ghazali, R., Deris, M. (eds) Recent Advances on Soft Computing and Data Mining. Advances in Intelligent Systems and Computing, vol 287. Springer, Cham. https://doi.org/10.1007/978-3-319-07692-8_35
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DOI: https://doi.org/10.1007/978-3-319-07692-8_35
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07691-1
Online ISBN: 978-3-319-07692-8
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