Method for realizing fast-speed short text bi-cluster

A short text, double clustering technology, applied in special data processing applications, instruments, electronic digital data processing, etc., can solve problems such as unreachable, poor results, and low clustering accuracy.

Active Publication Date: 2013-06-26
中科国力(镇江)智能技术有限公司
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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 ...

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  • Method for realizing fast-speed short text bi-cluster
  • Method for realizing fast-speed short text bi-cluster
  • Method for realizing fast-speed short text bi-cluster

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Embodiment Construction

[0036] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0037] Such as figure 1 As shown, a fast short text biclustering method includes the following steps:

[0038] Step 1) Preprocessing of short text distractors, with the support of irrelevant word dictionary and part of speech dictionary, quickly identify and process irrelevant words and part of speech for short text.

[0039] Step 2) Based on the short text similarity calculation, the preprocessed two short text similarities are calculated to form a short text similarity sparse matrix.

[0040] 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 settlement results of short text similarity.

[0041] Step 4) Perform secondary clustering of short texts on the basis of primary clustering results.

[0042] The above steps will b...

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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...

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Application Information

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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
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