Abstract
This paper presents a recommendation method of health articles based on association rules for health terms appeared on Web documents. On the Web search for health information, we sometimes find it difficult to decide which Web articles are relevant to our symptoms and reliable information. The proposed method classifies health articles and make scores on each article based on association rules, and then, recommends health articles with high support values according to user’s symptoms. In the experiment, we evaluate the feasibility of our proposed method.
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Thong, T.V., Takano, K., Li, K.F. (2022). A Recommendation Method of Health Articles Based on Association Rules for Health Terms Appeared on Web Documents and Their Application Systems. In: Barolli, L., Hussain, F., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2022. Lecture Notes in Networks and Systems, vol 451. Springer, Cham. https://doi.org/10.1007/978-3-030-99619-2_21
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DOI: https://doi.org/10.1007/978-3-030-99619-2_21
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