Abstract
Extracting the semantic relatedness of terms is an important topic in several areas, including data mining, information retrieval and web recommendation. This paper presents an approach for computing the semantic relatedness of terns in RDF graphs based on the notion of proximity. It proposes a formal definition of proximity in terms of the set paths connecting two concept nodes, and an algorithm for finding this set and computing proximity with a given error margin. This algorithm was implemented on a tool called Shakti that extracts relevant ontological data for a given domain from DBpedia - a community effort to extract structured data from the Wikipedia. To validate the proposed approach Shakti was used to recommend web pages on a Portuguese social site related to alternative music and the results of that experiment are also reported.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
