Hierarchy clustering method of successive dichotomy for document in large scale

Abstract

A method for clustering large-capacity text includes presenting vector space of text, calculating similarity between each two texts, embedding pattern into dimensional space and using K-means algorithm to cluster texts to be two types, carrying out successive bisect till requirement is satisfied and pattern is not divided any more.

Description

technical field [0001] The invention belongs to the technical field of text information, and in particular relates to a large-scale text clustering method. Background technique [0002] With the popularity of the Internet, more and more people like to use the Internet as a media for expressing their opinions. Many forums, blogs, and chat rooms provide a wealth of public opinion information, how to use computers to automatically analyze this information has become a very important issue. Text clustering is a technology that can use computers to automatically classify text information. After clustering, those articles belonging to the same topic will be classified into the same category, which is convenient for users to search and read. At present, there are mainly the following text clustering methods: [0003] 1. K-means is a fast clustering algorithm based on optimization criteria. The algorithm randomly finds k initial class centers at the beginning. Then assign each t...

AI Technical Summary

Problems solved by technology

The advantage of this algorithm is that the clustering effect is better, but the disadvantage is that the speed is very slow.

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