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    Document recommender agent based on hybrid approach

    Khalifa, C.; Chin, K. O.; Alfred, R.; Anthony, Patricia
    Abstract
    As Internet continues to grow, user tends to rely heavily on search engines. However, these search engines tend to generate a huge number of search results and potentially making it difficult for users to find the most relevant sites. This has resulted in search engines losing their usefulness. These users might be academicians who are searching for relevant academic papers within their interests. The need for a system that can assist in choosing the most relevant papers among the long list of results presented by search engines becomes crucial. In this paper, we propose Document Recommender Agent, that can recommend the most relevant papers based on the academician’s interest. This recommender agent adopts a hybrid recommendation approach. In this paper we also show that recommendation based on the proposed hybrid approach is better that the content-based and the collaborative approaches.... [Show full abstract]
    Keywords
    Document recommender agent; agent technology; information retrieval
    Fields of Research
    08 Information and Computing Sciences; 080704 Information Retrieval and Web Search; 0801 Artificial Intelligence and Image Processing
    Date
    2014-04
    Type
    Journal Article
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    • Department of Informatics and Enabling Technologies [109]
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    Document Recommender Agent Based on Hybrid.pdf
    DOI
    https://doi.org/10.7763/IJMLC.2014.V4.404
    Metadata
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    Copyright © 2008-2015. International Journal of Machine Learning and Computing. All rights reserved.
    Citation
    Khalifa, Chin, K., Rayner, & Patricia. (2014). Document Recommender Agent Based on Hybrid Approach. International Journal of Machine Learning and Computing, 4(2), 151-156. doi:10.7763/IJMLC.2014.V4.404
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