A Fast Short Text Biclustering Method

A short-text, double-clustering technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as low clustering accuracy, failure to reach, and poor results

Active Publication Date: 2016-04-27
中科国力(镇江)智能技术有限公司
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AI Technical Summary

Problems solved by technology

[0006] (2) Accurate calculation of short text similarity
At present, although there are many similarity algorithms (such as Euclidean distance method, cos distance method, Pearson coefficient method, VDM method, etc.), according to our research, they all have defects, and the effect is not good in practical applications.
[0007] (3) Fast and accurate clustering of short texts
Traditional single clustering (such as K nearest neighbor method, hierarchical clustering method, etc.) is difficult to achieve accurate clustering. When facing open corpus, the clustering accuracy is generally very low, which cannot meet the needs of practical applications.
Moreover, when the length of the short text is slightly higher, the clustering accuracy is lower

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  • A Fast Short Text Biclustering Method
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  • A Fast Short Text Biclustering Method

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Embodiment Construction

[0043] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0044] Such as figure 1 As shown, a fast short text biclustering method includes the following steps:

[0045] Step 1) Preprocessing of short text interference items, with the support of irrelevant word dictionary and part of speech dictionary, fast irrelevant word and part of speech recognition and processing recognition for short text.

[0046] Step 2) Calculating the similarity of short texts based on , calculating the similarity of two short texts after preprocessing to form a sparse matrix of similarity of short texts.

[0047] Step 3) Perform first-level clustering of short texts on the short text similarity sparse matrix, and divide similar short texts into clusters one by one according to the calculation results of short text similarity.

[0048] Step 4) Perform secondary clustering of short texts on the basis of primary clustering re...

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Abstract

The invention relates to a method for realizing fast-speed short text bi-cluster. The method comprises the following steps of: (1) preprocessing short text disturbance items, and carrying out fast-speed unrelated-language and word-class recognition and processing recognition on short texts with the support of an unrelated-language dictionary and a word-class dictionary; (2) calculating the similarity of two preprocessed short texts to form a short text similarity sparse matrix; (3) carrying out short text first-level clustering on the short text similarity sparse matrix, and dividing similar short texts into clusters one by one according to the calculation result of the short text similarity; and (4) carrying out second-level clustering on the basis of the result of the first-level clustering.

Description

technical field [0001] The invention relates to natural language processing in the field of artificial intelligence computers, in particular to a fast short text bi-clustering method and its realization by using natural language processing and data clustering. Background technique [0002] In a large number of natural language applications, there is a basic and common problem: for a corpus composed of short texts (hereinafter referred to as short text corpus or corpus), how to organize the short texts according to a certain similarity clustered into different classes. [0003] Generally speaking, the basic idea of ​​text clustering is to cluster "similar" texts into a class; in this class, the "differences" between texts are small. Texts that are not "similar" are clustered into other classes. The "gap" between different classes is large. Here, "similarity" / "gap" is a measure between some texts, which depends on different application requirements. There are many traditio...

Claims

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Application Information

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Patent Type & AuthorityPatents(China)
IPC IPC(8): G06F17/30G06F17/27
Inventor符建辉刘亮亮王石王卫民
Owner中科国力(镇江)智能技术有限公司