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An Automatic Text Label Extraction Method Combining Topic Model and Semantic Analysis

A technology of semantic analysis and topic model, applied in semantic analysis, natural language data processing, instruments, etc., can solve the problems of unrealistic labeling of training sets, time-consuming and laborious labeling, etc.

Active Publication Date: 2019-03-08
DATAGRAND TECH INC
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

However, the labeling of the training set is very time-consuming and laborious, and the subject of the document often changes drastically over time, so it is unrealistic to label the training set at any time

Method used

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  • An Automatic Text Label Extraction Method Combining Topic Model and Semantic Analysis
  • An Automatic Text Label Extraction Method Combining Topic Model and Semantic Analysis
  • An Automatic Text Label Extraction Method Combining Topic Model and Semantic Analysis

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Embodiment Construction

[0042] The present invention will be further described below in conjunction with accompanying drawing:

[0043] Such as figure 2 Shown: A text label automatic extraction method combining topic model and semantic analysis, including the following steps:

[0044] The first step: preprocessing;

[0045] Step 2: LDA modeling and context analysis;

[0046] The third step: label extraction.

[0047] The preprocessing method of the first step is: if there are low-frequency words, stop words and tag information, the preprocessing includes removing low-frequency words, removing stop words and removing tag information; the low-frequency words are only in one or two texts appear, the stop words are auxiliary words that carry almost no information, words that reflect the grammatical structure of the sentence, all function words, and punctuation marks; the markup information is web page text or other markup language text information; other markup language text information including htm...

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Abstract

The invention relates to an automatic extraction method for text labels in combination with theme model and semantic analyses, pertaining to the technical field of computer application. The method comprises pre-treatment, LDA modeling, context analyses and label extraction.The pre-treatment comprises following steps: removing low-frequency words, removing stop words and removing label information, wherein stop words are auxiliary words without any information, words showing sentence grammar structures, all function words and punctuations. The LDA modeling process comprises following steps: obtaining two matrixes after processing the LDA model: one is a file-theme matrix of N*K with each element corresponding to a hidden theme distribution of each file and the other is a K*M theme-word matrix with each element corresponding to a word distribution of each theme. Based on a conventional counting method, the method takes correlations of words in files into consideration and fully utilizes one key feature of context information so that label information of files is obtained.

Description

technical field [0001] The invention relates to a method for automatically extracting text labels by combining topic models and semantic analysis, and belongs to the technical field of computer applications. Background technique [0002] In the DT (data technology) era, Internet information is growing explosively, and various text data emerge in endlessly, such as diversified news and massive original articles from We Media. Faced with such a wealth of information, people urgently need some automated tools to help them accurately and quickly find the key information they need from the vast ocean of information. It is against this background that label extraction occurs. Tags are an important way to quickly obtain key information of texts and grasp themes, and have important applications in information retrieval, natural language processing, intelligent recommendation and other fields. Many websites provide users with the function of labeling objects of interest (such as pic...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/27
CPCG06F40/289G06F40/30
Inventor 于敬
Owner DATAGRAND TECH INC
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