Efficient Recommendation System based on Keyword for Smart-City with Sentiment Analysis using Hadoop
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2017 by IJETT Journal|
|Year of Publication : 2017|
|Authors : Ms. Sneha G. Potdar, Prof. N. S. More
|DOI : 10.14445/22315381/IJETT-V48P204|
Ms. Sneha G. Potdar, Prof. N. S. More "Efficient Recommendation System based on Keyword for Smart-City with Sentiment Analysis using Hadoop", International Journal of Engineering Trends and Technology (IJETT), V48(1),17-23 June 2017. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
In today’s life recommender system plays the important role while user is on social networking site, online shopping website. For presenting the personalized recommendation according to the new user’s demand is big challenge. The previous recommender system produces the recommendation without checking the personalized interest of user, due to that they couldn’t meet their proper requirement. In this paper, the recommender system works very efficiently using Hadoop by computing the reviews based on removing stop-words, stemming algorithm and sentiment analysis algorithm. Therefore, in the Smart-City application, the user getting accurate recommendation by computing reviews in positive, negative and neutral way according to new user’s keywords or sentences with the related services. Therefore, this paper approaches speed-up the performance over large amount of dataset using Map-Reduce. The proposed system puts forward an idea of aspect parsing technique and sentiment analysis technique which is forwarded with precision and recall measurement for an effective and accurate recommendation over reviews.
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Accuracy, Efficient, Keyword, Recommender System, Smart-City, Sentiment Analysis, Hadoop, Map-Reduce.