In some real-world areas, it is important to enrich the data with external background knowledge so as to provide context and to facilitate pattern recognition. These areas may be described as data rich but knowledge poor. There are two challenges to incorporate this biological knowledge into the data mining cycle: (1) generating the ontologies; and (2) adapting the data mining algorithms to make use of the ontologies. This chapter presents the state-of-the-art in bringing the background ontology knowledgeinto the pattern recognition task for biomedical data
88 p.Knowledge discovery in the biomedical domain is often restricted to structural relational data....
<div><p>Ontology matching is a growing field of research that is of critical importance for the sema...
Text mining in biomedicine can be used for several tasks relating both to the extraction of domain-s...
The explosion of biomedical data and the growing number of disparate data sources are exposing resea...
The explosion of biomedical data and the growing number of disparate data sources are exposing resea...
In recent years, there is an increasing demand for sharing and integration of medical data in biomed...
Le Web sémantique propose un ensemble de standards et d'outils pour la formalisation et l'interopéra...
In this chapter we provide a broad overview of selected knowledge management, data mining, and text ...
The explosive growth in the volume of data and the growing number of disparate data sources is bring...
The volume of biomedical literature is increasing at such a rate that it is becoming difficult to lo...
Ontologies are increasingly being used to provide background knowledge in machine learning models. W...
Ontology matching is a growing field of research that is of critical importance for the semantic web...
Abstract: The recent achievements in the Human Genome Project have made possible a high-throughput “...
Much of biology works by applying prior knowledge (`what is known') to an unknown entity, rathe...
Abstract. Data mining, which aims at extracting interesting informa-tion from large collections of d...
88 p.Knowledge discovery in the biomedical domain is often restricted to structural relational data....
<div><p>Ontology matching is a growing field of research that is of critical importance for the sema...
Text mining in biomedicine can be used for several tasks relating both to the extraction of domain-s...
The explosion of biomedical data and the growing number of disparate data sources are exposing resea...
The explosion of biomedical data and the growing number of disparate data sources are exposing resea...
In recent years, there is an increasing demand for sharing and integration of medical data in biomed...
Le Web sémantique propose un ensemble de standards et d'outils pour la formalisation et l'interopéra...
In this chapter we provide a broad overview of selected knowledge management, data mining, and text ...
The explosive growth in the volume of data and the growing number of disparate data sources is bring...
The volume of biomedical literature is increasing at such a rate that it is becoming difficult to lo...
Ontologies are increasingly being used to provide background knowledge in machine learning models. W...
Ontology matching is a growing field of research that is of critical importance for the semantic web...
Abstract: The recent achievements in the Human Genome Project have made possible a high-throughput “...
Much of biology works by applying prior knowledge (`what is known') to an unknown entity, rathe...
Abstract. Data mining, which aims at extracting interesting informa-tion from large collections of d...
88 p.Knowledge discovery in the biomedical domain is often restricted to structural relational data....
<div><p>Ontology matching is a growing field of research that is of critical importance for the sema...
Text mining in biomedicine can be used for several tasks relating both to the extraction of domain-s...