Sciweavers

Share
RECSYS
2009
ACM

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

9 years 2 months ago
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.
Dorothea Tsatsou, Fotis Menemenis, Ioannis Kompats
Added 23 Jul 2010
Updated 23 Jul 2010
Type Conference
Year 2009
Where RECSYS
Authors Dorothea Tsatsou, Fotis Menemenis, Ioannis Kompatsiaris, Paul C. Davis
Comments (0)
books