Smart Service Recommendation System by Applying MapReduce Techniques on Big Data

  Pallavi R. Desai,  Amol R. Dhakne

Now days, the amount of data in internet grown beyond the size of processing, this is Big Data. In the last few years, the information is growing vast, and separating this wide information, yielding the big data and analysis is major problem for recommender systems. Consequently, most of the traditional recommender systems frequently suffer from scalability and lack of accuracy problem and fails to meet personalized requirements. The purpose of Smart Service Recommender system is providing appropriate recommendations to users as per their interest and gives a recommendation list and recommending the most right items to the users. To improve its scalability, it is executed on Hadoop with MapReduce and Filtering algorithm is adopted to generate recommendations. Finally, general experiments are conducted on real-world data sets of movielens, and results demonstrate that Smart Service Recommendation System expressively recovers the accuracy and scalability of service recommender systems over existing approaches.

Keywords- Hadoop, Big Data, MapReduce, , recommender system, preference, keyword

Unique Identification Number - IJEDR1703047
Page Number(s) - 331-336
Pubished in - Volume 5 | Issue 3 | July 2017
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  Pallavi R. Desai,  Amol R. Dhakne,   "Smart Service Recommendation System by Applying MapReduce Techniques on Big Data", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.5, Issue 3, pp.331-336, July 2017, Available at :http://www.ijedr.org/papers/IJEDR1703047.pdf