Diversified and Scalable Recommendation System for the Web Services
| Author(s) | : | Neha Rakeshiya, Nitya khare |
| Institution | : | Student, Sagar Institute of Research and Technology excellence Bhopal |
| Published In | : | Vol. 4, Issue 9 — September 2017 |
| Page No. | : | 45-49 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
Web recommendation got an immense use in current technologies, where an analysis based decision is required indifferent field such as e-commerce, social media, service providers and other blog platform. In order to perform acompetitive analysis various tools are available. Also many research algorithm such as collaborative filtering, HMM, contentbased filtering, context based filtering is previously performed. Tools which are often using having limitation such asfunctionality or reporting, as well as they are often costly which cannot be used by every entity. Previous algorithm alsofinds limitations while computing accuracy and other relevant parameters. In this paper an efficient approach for findingrecommendation over web data is done. An experiment performed over a Generated telecom operator dataset using javaAPI. Algorithm computes efficient parameter while comparing with previous approach.
Neha Rakeshiya, Nitya khare, “Diversified and Scalable Recommendation System for the Web Services”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 4, Issue 9, pp. 45-49, September 2017.
