Hike the performance of collaborative filtering algorithm with the inclusion of multiple attributes

Автор: Barkha A. Wadhvani, Sameer A. Chauhan

Журнал: International Journal of Information Technology and Computer Science @ijitcs

Статья в выпуске: 4 Vol. 10, 2018 года.

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At a recent time, digital data increases very speedily from small business to large business. In this span of internet explosion, choices are also increases and it makes the selection of products very difficult for users so it demands some recommendation system which provides good and meaningful suggestions to users to help them to purchase or select products of their own choice and get benefited. Collaborative filtering technique works very productive to provide personalized suggestions. It works based on the past given ratings, behavior and choices of users to provide recommendations. To boost its performance many other algorithms and techniques can be combined with it. This paper describes the method to boost the performance of collaborative filtering algorithm by taking multiple attributes in consideration where each attribute has some weight.

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Recommendation system, Collaborative filtering algorithm, Multiple attributes, Distributed computation, Compute intensive tasks, TOPSIS, Hadoop

Короткий адрес: https://sciup.org/15016256

IDR: 15016256   |   DOI: 10.5815/ijitcs.2018.04.08

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  • Topsis, sept, 2017. Retrived from, https://en.wikipedia.org/wiki/TOPSIS
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