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Algorithms 2013, 6(3), 565-590; doi:10.3390/a6030565

An Emergent Approach to Text Analysis Based on a Connectionist Model and the Web

Department of Information Engineering, University of Pisa, Largo Lucio Lazzarino 1, Pisa 56122, Italy
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Received: 5 August 2013 / Revised: 5 September 2013 / Accepted: 10 September 2013 / Published: 17 September 2013
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Abstract

In this paper, we present a method to provide proactive assistance in text checking, based on usage relationships between words structuralized on the Web. For a given sentence, the method builds a connectionist structure of relationships between word n-grams. Such structure is then parameterized by means of an unsupervised and language agnostic optimization process. Finally, the method provides a representation of the sentence that allows emerging the least prominent usage-based relational patterns, helping to easily find badly-written and unpopular text. The study includes the problem statement and its characterization in the literature, as well as the proposed solving approach and some experimental use.
Keywords: natural language processing; language usage; emergent paradigm; unsupervised approach; connectionist model; web as corpus natural language processing; language usage; emergent paradigm; unsupervised approach; connectionist model; web as corpus
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Cimino, M.G.; Vaglini, G. An Emergent Approach to Text Analysis Based on a Connectionist Model and the Web. Algorithms 2013, 6, 565-590.

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