Information extraction and classification from free text using a neural approach

Authors:
Ignazio Gallo;Elisabetta Binaghi
Affiliations:
Department of Computer Science and Communication, Universitá degli Studi dell'Insubria, Varese, Italy;Department of Computer Science and Communication, Universitá degli Studi dell'Insubria, Varese, Italy
Venue:
CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
Year:
2007

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Abstract

Many approaches to Information Extraction (IE) have been proposed in literature capable of finding and extract specific facts in relatively unstructured documents. Their application in a large information space makes data ready for post-processing which is crucial to many context such asWeb mining and searching tools. This paper proposes a new IE strategy, based on symbolic and neural techniques, and tests it experimentally within the price comparison service domain. In particular the strategy seeks to locate a set of atomic elements in free text which is preliminarily extracted from web documents and subsequently classify them assigning a class label representing a specific product.