Text clustering method and device

Abstract

The embodiment of the invention provides a text clustering method and device, and solves the problem in the prior art that a text clustering way can not realize text clustering on a dependence grammar level. The text clustering method comprises the following steps of: identifying a dependence grammar relationship among terms in each text to be clustered of a text library; converting the dependence grammar relationship in each text to be clustered into syntactic encoding; calculating a similarity among the syntactic encodings of the text to be clustered in the text library; and according to the calculation result of the similarity, clustering the text to be clustered in the text library.

Description

technical field [0001] The invention relates to the technical field of semantic analysis, in particular to a text clustering method and device. Background technique [0002] As an important means to effectively organize, summarize and navigate text information, text clustering has attracted more and more researchers' attention. The existing text clustering method is to convert the text into a vector model, and then perform clustering based on the literal meaning of the words in the text. However, the same literal meaning may be expressed through a variety of dependency syntactic structures, some of which are more commonly used and some are less popular. Existing text clustering methods cannot cluster texts at the level of dependency syntax . [0003] For example, "How old are you?" and "How old are you?" have the same literal meaning, but they have different dependent syntactic structures, and the dependent syntactic structure of "How old are you?" is more commonly used. ...

AI Technical Summary

Problems solved by technology

[0004] In view of this, the embodiment of the present invention provides a text clustering method and device, which solves the problem that the text clustering methods in the prior art cannot achieve text clustering at the syntactic level

Images