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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.