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Prediction of User Queries Dynamically in Intelligent Query Answering Systems to Improve Relevance and Accuracy Using Recommendation Agents

Author(s):

Jayashree M.G , RNS Institute of Technology; Rajkumar R, RNS Institute of Technology

Keywords:

Recommendation Agents, Intelligent Query Answering Agent, User Model.

Abstract

Recommendation agents (RAs) are software agents that elicit the interests or preferences of individual consumers for products, either explicitly or implicitly and make recommendations accordingly. Recommendation Agents have the potential to support and improve the quality of the decisions consumers make when searching for and selecting products online. In this paper, a model of recommendation agents is proposed which query over distributed knowledge bases with heterogeneity for our web-based intelligent query answering systems. Ontologies which are the key technology used to describe the semantics of information exchange are also introduced. These Ontologies provide a shared and common understanding of a domain that can be communicated across people and application systems and thus help knowledge sharing and reuse. This model improves the relevance of the query results.

Other Details

Paper ID: IJSRDV2I4206
Published in: Volume : 2, Issue : 4
Publication Date: 01/07/2014
Page(s): 427-429

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