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A text matching method using a semantic parsing structure

A matching method and semantic parsing technology, applied in the field of text matching using semantic parsing structure, can solve problems such as inaccurate results of semantic similarity measurement, and achieve the effect of optimizing user experience and improving matching accuracy.

Active Publication Date: 2019-05-21
ZHONGAN INFORMATION TECH SERVICES CO LTD
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AI Technical Summary

Problems solved by technology

[0057] In text matching, due to the randomness of the grammatical results, the semantic similarity measurement results of two sentences are not accurate enough

Method used

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  • A text matching method using a semantic parsing structure
  • A text matching method using a semantic parsing structure
  • A text matching method using a semantic parsing structure

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Embodiment Construction

[0106] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings, but this is not intended to limit the present invention.

[0107] Text similarity is related to the similarities and differences between texts, and the higher the similarity, the greater the commonality and the smaller the differences between texts.

[0108] refer to figure 1 As shown, a text matching method using a semantic analysis structure disclosed in an embodiment of the present invention includes the following steps:

[0109] Step 1. Construction of the corpus module.

[0110] The source of the corpus usually comes from two sources: 1. Organize by specialized personnel, sort out and classify the business, and make the knowledge points into a corpus (in the question answering system, it may be a corpus with correct questions and answers), and at the same time, take into account the similarity between...

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Abstract

The invention discloses a text matching method using a semantic parsing structure. The method comprises the following steps: defining an initial corpus set Cqa and a supplementary corpus set Cq; defining Semantic structure DP-tree corresponding to text by using a semantic dependency analysis method; Defining a kernel function of the text and a metric function of text similarity based on the semantic structure; Carrying out kernel clustering on the text; obtaining an aggregated text class function(shown in the specification), wherein i = 1, 2, ..., M, q'ij is ni sample points which are selectedfrom each cluster and are closest to the cluster; And through manual audit, approving the Ci class and marking the Ci class with a specific tag Ti. According to the invention, syntactic analysis structures such as a syntactic structure are used as a comparison basis; A convolution kernel function theory and tree kernels (tree kernel, TK) are combined to define a kernel function representing the distance between two tree syntactic structures, and internal and external knowledge of syntactic similarity, word vectors, word sense networks and the like is introduced, so that the similarity betweentexts can be accurately judged.

Description

technical field [0001] The invention belongs to the field of artificial intelligence natural language processing (NLP), in particular to a text matching method utilizing a semantic analysis structure. Background technique [0002] Taking applications such as question answering systems, information retrieval, and extraction as examples, the current mainstream technology in the industry still includes text matching, that is, the business side will prepare a large amount of consulting (service) business-related corpus. Once the user makes a search request (question or search formula given in natural language), the robot will query (search) from the question-answer corpus through a specific text matching algorithm to obtain a list of candidate questions that are closest to the user's question, and consider the most According to the best matching score, different strategies are used to display the answers (answering directly, providing a list of answers, or informing the user tha...

Claims

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Application Information

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IPC IPC(8): G06F17/27G06F16/35
Inventor 倪博溢邹辉张永煦
Owner ZHONGAN INFORMATION TECH SERVICES CO LTD
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