International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Since Year 2012 | Open Access | Double Blind Reviewed

ISSN: 2319-7064




Downloads: 113

Survey Paper | Computer Science & Engineering | India | Volume 4 Issue 1, January 2015


A Survey Paper on Clustering-based Collaborative Filtering Approach to Generate Recommendations

Rohit C. Joshi | Ratnamala S. Paswan


Abstract: The rapid development of information technology takes our shopping into the orbit of information. With the network construction of resources, the amount of shopping resources increases rapidly. Collaborative filtering (CF) is a technique commonly used to build personalized recommendations on the Web. Some popular websites that make use of the collaborative filtering technology include Amazon, Netflix, iTunes, IMDB. The most important issue which influences the collaborative filtering recommendation accuracy is the so-called data sparseness. Data sparseness causes the system difficulty in determining the nearest neighbors of the target user accurately. Clustering can solve this problem to some extent. Grouping a set of physical or objects into classes of similar objects, this process is called as clustering. This paper presents the methods to generate recommendations using clustering-based collaborative filtering approach.


Keywords: Clustering, Collaborative Filtering, Data Sparseness, Personalized Recommendations, Nearest Neighbors


Edition: Volume 4 Issue 1, January 2015,


Pages: 1395 - 1398


How to Cite this Article?

Rohit C. Joshi, Ratnamala S. Paswan, "A Survey Paper on Clustering-based Collaborative Filtering Approach to Generate Recommendations", International Journal of Science and Research (IJSR), Volume 4 Issue 1, January 2015, pp. 1395-1398, https://www.ijsr.net/get_abstract.php?paper_id=SUB15471

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