This paper presents a framework for improving the image index obtained by automated image annotation. Within this framework, the technique of keyword combination is used for fast image re-indexing based on initial automated annotations. It aims to tackle the challenges of limited vocabulary size and low annotation accuracies resulting from differences between training and test collections. It i...

Genome annotation, the task of assigning a description to each discovered genome sequence, is an important activity within the process of sequencing. It relies on the use of ontologies to maintain a uniform vocabulary and to support interoperability of different information resources. Often, only the Gene Ontology (GO) is used in the annotation process, but the exploration of other ontologies, ...

We propose an automatic system for annotating accurately data tables extracted from the web. This system is designed to provide additional data to an existing querying system called MIEL, which relies on a common vocabulary used to query local relational databases. We will use the same vocabulary, translated into an OWL ontology, to annotate the tables. Our annotation system is unsupervised. It...

Collaborative tagging systems have emerged as a successful solution for annotating contributed resources to online sharing platforms, facilitating searching, browsing, and organising their contents. To aid users in the annotation process, several tag recommendation methods have been proposed. It has been repeatedly hypothesized that these methods should contribute to improve annotation quality ...

A novel method for automatic annotation of images is used with keywords from a generic vocabulary of concepts or objects combined with annotation-based retrieval of images. This can be done by using spatial hidden Markov model, in which states represent concepts. The parameters of this model are estimated from a set of manually annotated training images. An image in a large test collection is t...

MOTIVATION High-throughput technologies such as DNA sequencing and microarrays have created the need for automated annotation of large sets of genes, including whole genomes, and automated identification of pathways. Ontologies, such as the popular Gene Ontology (GO), provide a common controlled vocabulary for these types of automated analysis. Yet, while GO offers tremendous value, it also has...

Automated annotation of digital images remains a highly challenging task being used for indexing, retrieving, and understanding of large collections of image data. This paper presents an original extension of an image annotation model using an object oriented approach. The proposed model is an extension of an efficient annotation model called Cross Media Relevance Model. Image’s regions are des...

A musically meaningful vocabulary is one of the keystones in building a computer audition system that can model the semantics of audio content. If a word in the vocabulary is not clearly represented by the underlying acoustic representation, the word can be considered noisy and should be removed from the vocabulary. This paper proposes an approach to construct a vocabulary of predictive semanti...

MOTIVATION The Gene Ontology (GO) is a controlled vocabulary designed to represent the biological concepts pertaining to gene products. This study investigates the methods for identifying informative subsets of GO terms in an automatic and objective fashion. This task in turn requires addressing the following issues: how to represent the semantic context of GO terms, what metrics are suitable f...