Personalized facets for faceted search using wikipedia disambiguation and social network

The main aim of this paper is to deal with semantic search based on personalized facets using Wikipedia disambiguation data which can help to solve lexical ambiguity. User profile is learned from his/her activities and preferences in Facebook social network. Faceted graph visualization for result collaborative filtering is proposed. The facets are vertices representing ontological concepts. Other vertices represent instances belonging to the concepts, which are known as facets values. The vertices are highlighted by matching with user profile using TF-IDF feature vector model in order to individually produce search interfaces. The ties between vertices are ontological relations or properties considering as variables/attributes of facets. An algorithm to construct the faceted graph visualization and collaboratively filter search result is also provided. The faceted search method presented here is implemented to demonstrate these ideas. © Springer International Publishing Switzerland 2016.