A Specialized Recommender Agent for the Semantic Web
Neli P. Zlatareva · Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science · 2018
Information overload is one of the main challenges for web users nowadays.Intelligent Personal Assistants provide some help in dealing with this issue by navigating and collecting information, but they are not capable of meaningfully integrating and interpreting that information to address personalized user queries.Transition to the Semantic Web promises a dramatic shift in the scope of web services and the way they are performed.The so-called Semantic Recommender Systems utilize Semantic Web technologies to carry out a highly focused search based on similarities between concepts.This paper discusses a specialized recommender agent which derives contextual knowledge from targeted search on a simulated linked data network to provide personalized recommendations in the domain of interest.An extended example is followed throughout the paper to illustrate the type of queries the agent is intended to address.