Fuzzy Thesauri Recommendation System For Web 2.0 Social networks

Abstract

In the information age with billions of documents available on the Internet, searching among these documents has become quite a challenge for researchers. Since most of the search methods are based on terms within the documents, identifying the relationship between the terms has always been important in the eld of Information Retrieval. Using term relations in query expansion techniques is one of the most commonly used and successful approaches that are being used in order to help users nd what they need. In this study a fuzzy set based methodology is exploited for the retrieval and analysis of data available in Web2.0 social networking sites. The documents in each server or node are used for building a knowledge-base that will be employed by the Recommendation System in order to provide domain speci c suggestions, based on the friendship network in social networking sites. The results of the study show that the proposed methodology is reasonably scalable and can be employed on social networking sites.