Mapping WordNets using structural information
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Using Semantic Commonsense Resources in Image Retrieval
SMAP '06 Proceedings of the First International Workshop on Semantic Media Adaptation and Personalization
Toward a common semantics between media and languages
Proceedings of the 2006 international workshop on Research issues in digital libraries
Oracle in Image Search: A Content-Based Approach to Performance Prediction
ACM Transactions on Information Systems (TOIS)
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Search engines are among the most useful Internet applications. There exist several media types on the Web and, given the particularities of each of them, adapted search solutions are required. We limit our discussion to image search engines. While rapid and robust, existing image search engines offer results that respond only partially to the user's queries. An improvement of image search results might be obtained with the introduction of semantics in the dedicated systems. Here, we discuss the construction and the utilization of a multilingual lexical resources (WordNets in several languages) to improve image retrieval on the Internet. Given the initial nouns hierarchies in the WordNets, we build a multilingual OWL ontology including knowledge in English, Italian, and Spanish. A pictured representation of a dog remains a representation of a dog in spite of the associated name (would this be dog, perro or cane). The use of a large scale multilingual ontology allows us to offer the consequent sets of responses for the concepts in the hierarchy irrespective to the initial language the query was formulated in. With the use of an ontology to structure an image database, we can solve problems related to the ambiguity of a query content and we obtain an important gain in precision in the image sets rendered to the user compared to state of the art system.