A fuzzy preference tree-based recommender system for medical database

  • Authors

    • Pradeepini Gera
    • Vishnu Bhargavi Sabbisetty
    • Tejaswini Devarasetty
    • Madhusri Nukala
    • Navyasri Vittamsetty
    2017-12-21
    https://doi.org/10.14419/ijet.v7i1.1.9712
  • Comprehensive Tree Matching Method, Fuzzy Preference, Fuzzy Techniques, Fuzzy Tree-Established, Recommender System.

  • Abstract

    Nowadays every online site is using personalized recommender systems to suggest a right product for the customer. But existing system has tree structures and have unrequired items in the user preferences. So, it requires high memory and time. To overcome this issue,proposed a new method with increased performance. Firstly, introduced a technique for modeling fuzzy tree-established consumer pref-erences, in which fuzzy set techniques are used to express user choices. A recommendation approach to recommend tree-dependent items is then advanced. The critical path on this study is a comprehensive tree matching method, which can compare two tree-established facts and identify their corresponding components by taking into consideration of all the records on tree structures, weights, and the nodeattributes.The proposed fuzzy preference tree based recommender system is tested using a medical dataset.

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  • How to Cite

    Gera, P., Bhargavi Sabbisetty, V., Devarasetty, T., Nukala, M., & Vittamsetty, N. (2017). A fuzzy preference tree-based recommender system for medical database. International Journal of Engineering & Technology, 7(1.1), 319-321. https://doi.org/10.14419/ijet.v7i1.1.9712

    Received date: 2018-02-25

    Accepted date: 2018-02-25

    Published date: 2017-12-21