Abstract
Discovering significant meta-information from document collections is a critical factor for knowledge distribution and preservation. This paper presents a system that implements intelligent document processing techniques, by combining strategies for the layout analysis of electronic documents with incremental first-order learning in order to automatically classify the documents and their layout components according to their semantics. Indeed, an in-deep analysis of specific layout components can allow the extraction of useful information to improve the semantic-based document storage and retrieval tasks. The viability of the proposed approach is confirmed by experiments run in the real-world application domain of scientific papers.
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Esposito, F., Ferilli, S., Basile, T.M.A., Di Mauro, N. (2005). Semantic-Based Access to Digital Document Databases. In: Hacid, MS., Murray, N.V., Raś, Z.W., Tsumoto, S. (eds) Foundations of Intelligent Systems. ISMIS 2005. Lecture Notes in Computer Science(), vol 3488. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11425274_39
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DOI: https://doi.org/10.1007/11425274_39
Publisher Name: Springer, Berlin, Heidelberg
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