A Multi-Layered Bayesian Network Model for Structured Document Retrieval
Identificadores
URI: https://hdl.handle.net/10481/77878Metadatos
Mostrar el registro completo del ítemAutor
Crestani, Fabio; Campos Ibáñez, Luis Miguel; Fernández Luna, Juan Manuel; Huete Guadix, Juan FranciscoEditorial
Springer
Materia
Inteligencia artificial Artificial intelligence
Fecha
2003Referencia bibliográfica
Published version: Crestani, F... [et al.] (2003). A Multi-layered Bayesian Network Model for Structured Document Retrieval. In: Nielsen, T.D., Zhang, N.L. (eds) Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2003. Lecture Notes in Computer Science(), vol 2711. Springer, Berlin, Heidelberg. [https://doi.org/10.1007/978-3-540-45062-7_6]
Patrocinador
Spanish CICYT and FIS, under Projects TIC2000-1351 and PI021147; European Commission under the IST Project MIND (IST-2000-26061)Resumen
New standards in document representation, like for example
SGML, XML, and MPEG-7, compel Information Retrieval to design and
implement models and tools to index, retrieve and present documents
according to the given document structure. The paper presents the de-
sign of an Information Retrieval system for multimedia structured doc-
uments, like for example journal articles, e-books, and MPEG-7 videos.
The system is based on Bayesian Networks, since this class of mathe-
matical models enable to represent and quantify the relations between
the structural components of the document. Some preliminary results on
the system implementation are also presented.