(E-AggNN) Implementation of Effective and Efficient Algorithm Collaborative Filtering and Content Based similarity Search on Recommender System

Computer Science and Engineering

In this work, we used sum variant of FANN, and other for the max variant. Here investigates a novel technique to solve a “cold start” problem. This problem occurs when new item added in the list means there is null score assign to that particular item our aim is to provide solution that is manufacturer and customer oriented. Our result generates recommendations as per the manufacture and Customer oriented using collaborative filtering and ranking based mechanism.For better and fast performance nowadays all the search engines are enhanced with recommendation system. Most of the time Recommendation process depends on the past entities, so collaborative filtering technique uses this past data for recommending process. Collaborative filtering alone is not able to provide fine grained recommendation for all the users’ queries. Hybrid Recommendation system is required which uses both past and present data which are aggregated for the high dimensional parameters.

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