Paper Info
Title
A semantic framework for personalized ad recommendation based on advanced textual analysis
Abstract
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.
Year
DOI
Venue
2009
10.1145/1639714.1639752
RecSys
Keywords
Field
DocType
advanced textual analysis,semantic framework,content-extracted linguistic information,hybrid recommendation system,semantic knowledge,semantic profile,personalized ad recommendation,fuzzy semantic reasoning,ontological knowledge,real world user study,ontological user profile,system architecture,advertising scenario,knowledge base,distributed system,recommender system
Semantic memory,Ontology (information science),Recommender system,Rule-based machine translation,Ontology,Semantic framework,Data mining,Architecture,Information retrieval,Computer science,Fuzzy logic
Conference
Citations 
PageRank 
References 
6
0.47
8
Authors
4
Name
Order
Citations
PageRank
Dorothea Tsatsou1222.90
Fotis Menemenis2171.48
Ioannis Kompatsiaris31404197.36
Paul C. Davis4152.04