An Efficient and Dynamic Service Recommendation by Active Customer Preferences

  J. Frieda,  K.Aravindkumar

Recommendation system act as a device in providing most suitable facility to the user. At present, information through online services increases. This leads to the overhead of data in online and there is a chance of reaching less perfect results. In this paper “AN EFFICIENT AND DYNAMIC SERVICE RECOMMENDATION BY ACTIVE CUSTOMER PREFERENCES” using the active customer preferences. In previous approaches, recommendation of service is stand on the feedbacks and ranking from the preceding user. It doesn’t consider the idea of the user at a time, who in need of penetrating for the particular service. The proposed system deals with the implementation of personalized recommendation to provide services for hotel reservation system. Preferences are collected from the active user about particular service for each application. Similar user’s opinions are taken from the reviews using keyword extraction method and Supervised learning algorithms are used to identify sentiment orientation. It determines positive or negative opinion along with negation word near to each opinion word and then identifies the number of positive and negative opinions of reviews. Keywords with positive opinion are considered and similarity is calculated between user preferences with reviews of the previous user by accord and cosine measures. From this most similar keywords are provided to the user as recommended service. To provide more accurate prediction of the services needed by the active user the proposed system is implemented using Map Reduce framework. The large amount of data can be recovered by using Map Reduce from the investigation of queries meritoriously. The makeable technique for scheduling diminish responsibilities with the help of joining them into the effective characteristic by the well-organized set of guidelines.

Keywords- Edge-based active contour, edge-stop function, gradient information, image segmentation

Unique Identification Number - IJEDR1802078
Page Number(s) - 450-454
Pubished in - Volume 6 | Issue 2 | April 2018
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  J. Frieda,  K.Aravindkumar,   "An Efficient and Dynamic Service Recommendation by Active Customer Preferences", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.6, Issue 2, pp.450-454, April 2018, Available at :http://www.ijedr.org/papers/IJEDR1802078.pdf