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              <text>Comparative study of recommender systems</text>
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              <text>Content Based Filtering; Item-based Collaborative Filtering; Matrix Factorization; Recommender Systems; User-based Collaborative Filtering</text>
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              <text>Recommendation System is a quickly progressing study area. Many new approaches are offered so far. In this particular paper we have researched on various applications of recommender system and various techniques used in recommender system like collaborative filtering, content-based filtering and hybrid filtering. Collaborative filtering is amongst the common methods utilized in recommending process. So comparative study on various collaborative filtering is done and the results are plotted graphically.  2016 IEEE.</text>
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              <text>Thomas A.; Sujatha A.K.</text>
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              <text>Proceedings of IEEE International Conference on Circuit, Power and Computing Technologies, ICCPCT 2016</text>
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              <text>Institute of Electrical and Electronics Engineers Inc.</text>
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              <text>2016-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1109/ICCPCT.2016.7530304" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/ICCPCT.2016.7530304&lt;/a&gt;
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              <text>Restricted Access</text>
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              <text>ISBN: 978-150901277-0</text>
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              <text>English</text>
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              <text>Thomas A., Dept. of CSE, Faculty of Engineering, Christ University, Bengaluru, India; Sujatha A.K., Dept. of CSE, Faculty of Engineering, Christ University, Bengaluru, India</text>
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