New techniques used in automated text analysis
Automated analysis of natural language texts is one of the most important knowledge discovery tasks for any organization. According to Gartner Group, almost 90% of knowledge available at an organization today is dispersed throughout piles of documents buried within unstructured text. Analyzing huge volumes of textual information is often involved in making informed and correct business decisions. Traditional analysis methods based on statistics fail to help processing unstructured texts and the society is in search of new technologies for text analysis. There exist a variety of approaches to the analysis of natural language texts, but most of them do not provide results that could be successfully applied in practice. This article concentrates on recent ideas and practical implementations in this area.
Year of publication: |
2010
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Authors: | ISTRATE, Mihai |
Published in: |
Annals - Economy Series. - Facultatea de Ştiinţe Economice şi Gestiunea Afacerilor, ISSN 1844-7007. - Vol. 4.I.2010, December, p. 222-232
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Publisher: |
Facultatea de Ştiinţe Economice şi Gestiunea Afacerilor |
Subject: | text mining | text analysis | neural network |
Saved in:
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