Clustering XML Documents Using Structure and Content based on a New Similarity Function OverallSimSUX
Título del documento: Clustering XML Documents Using Structure and Content based on a New Similarity Function OverallSimSUX
Revue: Computación y sistemas
Base de datos: PERIÓDICA
Número de sistema: 000383413
ISSN: 1405-5546
Autores: 1
1
1
Instituciones: 1Universidad Central "Marta Abreu" de Las Villas, Departamento de Ciencias de la Computación, Villa Clara. Cuba
Año:
Periodo: Ene-Mar
Volumen: 19
Número: 1
Paginación: 151-162
País: México
Idioma: Inglés
Tipo de documento: Artículo
Enfoque: Analítico, descriptivo
Resumen en inglés Every day more digital data in semi-structured format are available on the World Wide Web, corporate intranets, and other media. Knowledge management using information search and processing is essential in the field of academic writing. This task becomes increasingly complex and defiant, mainly because collections of documents are usually heterogeneous, big, diverse, and dynamic. To resolve these challenges it is essential to improve management of time necessary to process scientific information. In this paper, we propose a new method of automatic clustering of XML documents based on their content and structure, as well as on a new similarity function OverallSimSUX which facilitates capturing the degree of similarity among documents. Evaluation of our proposal by means of experiments with data sets showed better results than those in previous work
Disciplinas: Ciencias de la computación,
Bibliotecología y ciencia de la información
Palabras clave: Tecnología de la información,
Gestión del conocimiento,
Documentos electrónicos,
Agrupamiento,
Similitud,
XML,
Análisis de contenido
Keyword: Computer science,
Library and information science,
Information technology,
Knowledge management,
Electronic documents,
Clustering,
Similarity,
XML,
Content analysis
Texte intégral: Texto completo (Ver HTML)