WEBSOM - Self-organizing maps of document collections

被引:194
作者
Kaski, S [1 ]
Honkela, T [1 ]
Lagus, K [1 ]
Kohonen, T [1 ]
机构
[1] Aalto Univ, Neural Networks Res Ctr, FIN-02015 Helsinki, Finland
基金
芬兰科学院;
关键词
data mining; information retrieval; self-organizig map; SOM; WEBSOM;
D O I
10.1016/S0925-2312(98)00039-3
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With the WEBSOM method a textual document collection may be organized onto a graphical map display that provides an overview of the collection and facilitates interactive browsing. Interesting documents can be located on the map using a content-directed search. Each document is encoded as a histogram of word categories which are formed by the self-organizing map (SOM) algorithm based on the similarities in the contexts of the words. The encoded documents an 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. (C) 1998 Elsevier Science B.V. All rights reserved.
引用
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页码:101 / 117
页数:17
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