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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
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Student Project, Computer Science & Engineering, India, Volume 11 Issue 6, June 2022
Pages: 1875 - 1880Microclustering with Outlier Detection for DADC
Aswathy Priya M.
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Analysis Study Research Paper, Computer Science & Engineering, India, Volume 12 Issue 11, November 2023
Pages: 1840 - 1846Analysis of Placement for Electronics and Communication Engineering Students using Multiple Clustering
Dr. Dola Sanjay S