A probabilistic, text and knowledge-based image retrieval system

Authors:
Rubén Izquierdo-Beviá;David Tomás;Maximiliano Saiz-Noeda;José Luis Vicedo
Affiliations:
Departamento de Lenguajes y Sistemas Informáticos, Universidad de Alicante, Spain;Departamento de Lenguajes y Sistemas Informáticos, Universidad de Alicante, Spain;Departamento de Lenguajes y Sistemas Informáticos, Universidad de Alicante, Spain;Departamento de Lenguajes y Sistemas Informáticos, Universidad de Alicante, Spain
Venue:
CLEF'05 Proceedings of the 6th international conference on Cross-Language Evalution Forum: accessing Multilingual Information Repositories
Year:
2005

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Natural language processing for information retrieval

Communications of the ACM
The CLEF 2005 cross–language image retrieval track

CLEF'05 Proceedings of the 6th international conference on Cross-Language Evalution Forum: accessing Multilingual Information Repositories

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Abstract

This paper describes the development of an image retrieval system that combines probabilistic and ontological information. The process is divided in two different stages: indexing and retrieval. Three information flows have been created with different kind of information each one: word forms, stems and stemmed bigrams. The final result combines the results obtained in the three streams. Knowledge is added to the system by means of an ontology created automatically from the St. Andrews Corpus. The system has been evaluated at CLEF05 image retrieval task.