Multi-model fused short text classification method

Abstract

The invention discloses a multi-model fused short text classification method. The multi-model fused short text classification method comprises a learning method and a classification method. The learning method comprises the following steps: carrying out word segmentation and filtration on short text training data to obtain a word set; calculating the IDF value of each word; calculating the TFIDF values of all the words and constructing a text vector VSM; and carrying out text learning on the basis of a vector space model, and constructing an ontology tree model, a keyword overlapping model, a naive Bayesian model and a support vector machine model. The classification method comprises the following steps: carrying out word segmentation and filtration on a to-be-classified short text; generating a text vector on the basis of the support vector machine model; respectively classifying by using the ontology tree model, the keyword overlapping model, the naive Bayesian model and the support vector machine model to obtain single model classification results; and fusing the single model classification results to obtain a final classification result. According to the method disclosed in the invention, multiple classification modes are fused and the short text classification correctness is improved.

Description

【Technical field】 [0001] The invention belongs to the field of intelligent information processing and computer technology, and in particular relates to a short text classification method. 【Background technique】 [0002] With the rapid development of the Internet, various network applications have penetrated into all aspects of social life. Various social applications represented by Weibo and WeChat, as well as various online comment and feedback mechanisms have become important channels for publishing and obtaining information in modern society. On Weibo, netizens can express their feelings, experiences, and perceptions, the government can release announcements and various information, and people can freely express their views and opinions on certain things, etc. [0003] Data such as Weibo, WeChat, and online comments are all text information with a limited number of words. These data are typical text passages, ie short texts. By mining the short text data of Weibo, it i...

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However, the adaptability and classification effect of these single clas

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