WDM: A New Efficient Visualization Method of Classifying Web Documents Based on SOM

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Abstract
We propose a new visualization method WDM to classify documents by adding in the position-factors of words such as the title-factor and the first-sentence-factor based on a SOM neural network. We also discuss the selection of the function which is used to calculate the belong-to-probability in neurons' reflecting process. The experimental results indicate that WDM makes the boundaries of different documents greatly more clear, and thus it can produce more accurate and intuitive classification compared to the visualization methods which do not have position-factors considered