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A short text classification method based on tf-idf feature extraction

A TF-IDF and feature extraction technology, which is applied in the field of data processing, can solve problems such as technical solutions that cannot achieve solutions, and achieve the effect of improving algorithm performance and enhancing weight

Active Publication Date: 2018-05-25
广东广业开元科技有限公司
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Problems solved by technology

If these external resources cannot be obtained, and there are not enough internal resources to pre-establish thesaurus and training word vector dictionary, these technical solutions cannot achieve a good solution

Method used

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  • A short text classification method based on tf-idf feature extraction
  • A short text classification method based on tf-idf feature extraction
  • A short text classification method based on tf-idf feature extraction

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Embodiment Construction

[0028] The specific embodiment of the present invention will be further described below in conjunction with accompanying drawing:

[0029] refer to image 3 , a short text classification method based on TF-IDF feature extraction, including the following steps:

[0030] Step A: Dataset annotation and preprocessing

[0031] Extract short text data from the overall data set as the training data of the SVM classifier, classify and label the extracted data according to the classification requirements, and then perform word segmentation to divide the short text data into multiple words;

[0032] Further as a preferred embodiment, in the step A, a stuttering word segmentation method is used for word segmentation.

[0033] Step B: Compute the TFIDF vector for classification enhancement

[0034] Extract data according to the classification and labeling of the above steps, and randomly divide the data in each category into two groups according to the proportion, as the training set a...

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Abstract

The invention discloses a TF-IDF feature extraction based short text classification method. According to the method, short texts are merged into a long text so as to enhance the TF-IDF feature of the short texts; dimension reduction is performed so as to generate a feature word list and a feature word dictionary; a mechanism compensation is established for a class having a relative unobvious feature while the feature word list is established, and the text feature vector weight is enhanced; and other word banks or word vector dictionaries do not have to be constructed or trained, and then the algorithm performance can be improved on the premise of ensuring the feature expression result of the texts. The TF-IDF feature extraction based short text classification method can be widely applied to the field of data processing.

Description

technical field [0001] The invention relates to the field of data processing, in particular to a short text classification method based on TF-IDF feature extraction. Background technique [0002] With the rise of social media, short texts such as mobile SMS, Tweet and Weibo have emerged in an endless stream. Due to the large number of participants and the rapid release frequency, the scale of short texts has grown rapidly. In addition, short text plays an important role in fields such as search engines, automatic question answering, and topic tracking. Moreover, with the implementation and deepening of e-government construction, government departments are also faced with the problem of dealing with a large number of short texts. However, due to the short text content is less and the features are not obvious, so in the processing of short text data, how to realize the simple and effective classification of a large number of short text data is of great significance. [0003...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30
CPCG06F16/355G06F16/36
Inventor 纪晓阳孔祥明林成创蔡斯凯蔡禹贾义动
Owner 广东广业开元科技有限公司
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