A semantic framework for personalized ad recommendation based on advanced textual analysis

In this paper we present a hybrid recommendation system that combines ontological knowledge with content-extracted linguistic information, derived from pre-trained lexical graphs, in order to produce high quality, personalized recommendations. In the described approach, such recommendations are exemplified in an advertising scenario. We propose a distributed system architecture that uses semantic knowledge, based on terminologically enriched domain ontologies, to learn ontological user profiles and consequently infer recommendations through fuzzy semantic reasoning. A real world user study demonstrates the improvements attained in providing user-relevant recommendations with the aid of semantic profiles. Categories and Subject Descriptors H.3.4 [Information Storage and Retrieval]: Systems and Software – Distributed systems. General Terms Algorithms. Keywords Ad recommendation, ontology population, lexical graph, ontological user profile, fuzzy reasoning.

• Type: Conference
• Year: 2009
• Where: RECSYS
• Authors: Dorothea Tsatsou, Fotis Menemenis, Ioannis Kompatsiaris, Paul C. Davis
• Keywords: Fuzzy Semantic Reasoning, Lexical Graph, Ontological User Profile, RECSYS 2009