Method for rapidly clustering documents

Abstract

The invention provides a fast document clustering method. The method is realized by the following steps: 1, a group of key words is extracted from each document by word frequency statistics; 2, the document is expressed to be a corresponding dimensional congregation of index value, the contained key words of the document are in the characteristic space of the congregation; 3, a nerve element in a self organization mapping model is expressed as a vector in the characteristic space; 4, the documents are input in sequence, and the similarity between the documents and all nerve elements is calculated; 5, the nerve element with maximum accumulated value is the winner; the winner and neighbor nerve elements adjust weight in current document direction; 6, an individual dimension that the nerve element is matched with the input document is adjusted while the weight of other dimensions are weakened; 7, all the documents are input, and the method is over. The invention utilizes a self-organization mapping clustering model to renovate the links of document quantization expression and similarity calculation, thus the calculation efficiency is greatly improved under the condition that the number of the documents is same and the clustering quality is maintained.

Description

(1) Technical field [0001] The invention relates to a document clustering technology, in particular to a fast document clustering method. (2) Background technology [0002] With the increasing popularity of the network and the remarkable achievements of information construction, people often need to face an astonishing number of natural language documents. The prominent problem is how to organize, concentrate and integrate the rich information and knowledge contained in them quickly and effectively. Processing, in order to improve the ability of human beings to grasp these massive amounts of information, and improve the level of cognition. Especially in recent years, the automatic sorting of users' personal documents, large-scale network information public opinion monitoring, topic tracking and detection technology, network public opinion trend tracking, and automatic classification of a large number of forum documents are inseparable from fast and high-quality research. Su...

AI Technical Summary

Problems solved by technology

[0004] The present invention provides a fast document clustering method to overcome the efficiency and low problems of existing clustering methods due to high-dimensional feature quantization and frequent similarity calculations

Images