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Paper Title
A review: Recommender System using Collaborative Filtering and Gray Sheep Problem
  Rajatha Prabhu,  Pooja Shetty,  Shilpa,  Shwetha D R,  Ramakrishna Hegde

Recommender system is a powerful process that plays an important role in the online marketing system. The recommendation technique used has become one of the important tools of personal service in website. The recommender systems are classified into three main categories: content-based, collaborative and hybrid recommendation approaches. Recommender system act as the bridge gap between the customers and the applications or websites by providing many options from which the customers make their choice of interest. In designing such recommenders designers face several problems. This review paper provides different methods to solve gray sheep problems. This can be used for the further research of fine-tuning and designing high quality recommender system.

Keywords- recommender system, content-based, collaborative, hybrid recommendation, clustering algorithms.
Publication Details
Unique Identification Number - IJEDR1802075
Page Number(s) - 440-443
Pubished in - Volume 6 | Issue 2 | April 2018
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Rajatha Prabhu,  Pooja Shetty,  Shilpa,  Shwetha D R,  Ramakrishna Hegde,   "A review: Recommender System using Collaborative Filtering and Gray Sheep Problem", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.6, Issue 2, pp.440-443, April 2018, Available at :http://www.ijedr.org/papers/IJEDR1802075.pdf
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