Developing an Ontological approach to Content-based Recommendation System

Abstract

During past decade the no of web user increases so rapidly leading to rapid increase in web services which leads to increase the usage data at higher rate. The usage data of these users now amount to be in order of Peta Byte (1015 bytes). In such cases the search space for user‟s queries increases and a user‟s search query may leads to retrieval of irrelevant information. Sometime the search algorithm may become exhaustive. This project is aimed to use User‟s context information to model a framework which can filter the search space and choose some preference based on user‟s context. The project follows a set of processes for profile construction of Users and Items, and determining their similarity and scoring their preference. The projects also compares the effectiveness in predicting User‟s preferences and accuracy in it with various other Collaborative approach such as User-Based model and Item based model to check its performance level and quality of predictions.