Authors:
Ghada Feki
;
Anis Ben Ammar
and
Chokri Ben Amar
Affiliation:
University of Sfax, Tunisia
Keyword(s):
Diversity, Semantic, Ambiguity, Image Retrieval, Wikipedia.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Business Analytics
;
Concept Mining
;
Data Analytics
;
Data Engineering
;
Information Extraction
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Mining Multimedia Data
;
Soft Computing
;
Symbolic Systems
;
Visual Data Mining and Data Visualization
;
Web Mining
Abstract:
In recent years, the explosive growth of multimedia databases and digital libraries reveals crucial problems in indexing and retrieving images, what led us to develop our own approach. Our proposed approach TAD consists in disambiguating web queries to build an adaptive semantic for diversity-based image retrieval. In fact, the TAD approach is a puzzle constituted by three main components which are the TAWQU (Thesaurus-Based Ambiguous Web Query Understanding) process, the ASC (Adaptive Semantic Construction) process and the DR (Diversity-based Retrieval) process. The Wikipedia pages represent our main source of information. The NUS-WIDE dataset is the bedrock of our adaptive semantic. Actually, it permits us to perform a respectful evaluation. Fortunately, the experiments demonstrate promising results for the majority of the twelve ambiguous queries.