The Research of Self-Organizing Maps Based on Document Collections

Yi Ding; Xian Fu

doi:10.4028/www.scientific.net/AMR.430-432.1232

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 430-432The Research of Self-Organizing Maps Based on...

The Research of Self-Organizing Maps Based on Document Collections

Abstract:

Web text mining is a new issue in the knowledge discovery research field. It is aimed to help people discover knowledge from large quantities of semi-structured or unstructured text in the web. Several approaches, including some pure and hybrid information retrieval (IR) methods, have been proposed to tackle such an issue. Among these approaches, combining the Self-Organizing Map (SOM) method with the principles of the vector-space model, appears to be a promising alternative for the traditional purely IR-based methods in this problem domain. The encoded documents are organized on another self-organizing map, a document map, on which nearby locations contain similar documents. Special consideration is given to the computation of very large document maps which is possible with general-purpose computers if the dimensionality of the word category histograms is first reduced with a random mapping method and if computationally efficient algorithms are used in computing the SOMs.

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Periodical:

Advanced Materials Research (Volumes 430-432)

Pages:

1232-1235

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.430-432.1232

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Online since:

January 2012

Authors:

Yi Ding, Xian Fu

Keywords:

Data Mining (DM), Document Collections, SOM, WEBSOM

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References

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