International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Semantic Based Document Recommendation System

Author : Athulya R Krishnan ¹ Remya R ²

Date of Publication :7th February 2016

Abstract: The objective of a recommender system is to generate relevant recommendations for the users. It is an information filtering technique that assists users by filtering the redundant and unwanted data from a data chunk and delivers relevant information to the users. An information system is known as recommendation engine when the delivered information comes in the form of suggestions. The information filtering system must be personalized in connection with the accommodation of different user’s interests. Usually recommender systems are based on the keyword search which allows the efficient scanning of very large document collections. The goal of document recommendation is entirely different from product recommendation to consumers. This paper addresses the problem of keyword extraction from conversations, and hence uses these keywords to retrieve, for each short conversation fragment, a small number of potentially relevant documents, which could then be recommended to the participants. Here analyses the problem area of the existing approaches in the keyword extraction and database search domains. The manual extraction of keywords is slow, expensive and bristling with mistakes. To overcome these scenarios here propose a new strategy, which is based on semantic meaning. It promises the solution for a document recommender system to be used in conversations.

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