A Clustering Based Hybrid Recommendation System for Services in Big Data
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 112 | Views: 361

Research Paper | Computer Science & Engineering | India | Volume 5 Issue 6, June 2016 | Popularity: 6.9 / 10


     

A Clustering Based Hybrid Recommendation System for Services in Big Data

Powar Gayatri Ashok, Dr. D. M. Yadav


Abstract: Big data deals with large volume of complex growing data set with multiple autonomous sources. With the growing technologies, data storage and data collection capacity goes increases day-by-day, big data are now rapidly expanding in all fields. It tends to increase services on internet. So, the service relevant data become too vast to process by traditional approaches. It becomes difficult for users to select best product from so many products which are available. These systems suffer from scalability, data sparsity, and cold-start problems resulting in poor quality recommendations. In order to view this problem this paper provides a hybrid recommendation system which will satisfy the users according to their needs and interest and increase the overall performance of the system. The main idea is using hybrid recommendation techniques to suppress the drawbacks of the traditional techniques or an individual technique in a combined model. Paper presents a system to improve the accuracy of recommendation in big data application.


Keywords: Big data, Clustering, Collaborative Filtering, Hybrid Recommendation system


Edition: Volume 5 Issue 6, June 2016


Pages: 1911 - 1915


DOI: https://www.doi.org/10.21275/NOV164280


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Powar Gayatri Ashok, Dr. D. M. Yadav, "A Clustering Based Hybrid Recommendation System for Services in Big Data", International Journal of Science and Research (IJSR), Volume 5 Issue 6, June 2016, pp. 1911-1915, https://www.ijsr.net/getabstract.php?paperid=NOV164280, DOI: https://www.doi.org/10.21275/NOV164280

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