Sentence semantic similarity calculation method

A technology of semantic similarity and calculation method, applied in the field of sentence semantic similarity calculation

Active Publication Date: 2017-10-24
湖南星汉数智科技有限公司
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AI Technical Summary

Problems solved by technology

[0006] Purpose of the invention: In order to solve the technical problems existing in the existing sentence semantic similarity calculation method, a sentence semantic similarity calculation method is provided. The two methods complement each other, making the feature extraction more comprehensive and accurate.

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Embodiment 1

[0064] refer to figure 1 , the present embodiment discloses a sentence semantic similarity calculation method, including the following process:

[0065] Step 1: Extract the features of the first sentence and the second sentence through the deep learning model and feature engineering respectively, and obtain the global semantic vector of the first sentence and the global semantic vector of the second sentence, as well as the local semantic vector of the first sentence and the local semantic vector of the second sentence semantic vector;

[0066] Step 1.1: Use the deep learning model to extract the features of the first sentence and the second sentence respectively, and obtain the global semantic vector of the first sentence and the global semantic vector of the second sentence. The specific process is as follows:

[0067] Step 1.1.1: Perform word vectorization representation of the sentence to obtain the word vector of the sentence; the sentence is the first sentence or the se...

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Abstract

The invention discloses a sentence semantic similarity calculation method which includes the steps: extracting characteristics of a first sentence and a second sentence by a deep learning model to obtain a first sentence global semantic vector and a second sentence global semantic vector; extracting characteristics of words of the first sentence and the second sentence through characteristic engineering to obtain a first sentence local semantic vector and a second sentence local semantic vector; splicing the first sentence global semantic vector and the second sentence global semantic vector with the first sentence local semantic vector and the second sentence local semantic vector to obtain a first sentence one-dimensional characteristic vector and a second sentence one-dimensional characteristic vector; calculating the vector distance between the first sentence one-dimensional characteristic vector and the second sentence one-dimensional characteristic vector to obtain similarity between the first sentence and the second sentence. Sentence characteristics extracted by the method are more comprehensive and deeper and have certain pertinence, and calculated similarity is higher in accuracy.

Description

technical field [0001] The invention relates to the field of natural language processing, in particular to a method for calculating sentence semantic similarity. Background technique [0002] Semantic similarity calculation is the most basic and widely used technology in text processing. From the word level, there are problems such as polysemy and ambiguity; from the sentence level, the sentence structure of the sentence is flexible and changeable, not as simple as the accumulation of words. Therefore, studying semantic similarity calculation is helpful for better semantic understanding. Semantic understanding has always been a difficult problem in the field of natural language processing, and it plays a vital role in many studies. For example, information retrieval, text clustering, paraphrase recognition, machine translation, automatic question answering, user intent understanding, etc. In the field of search (search engines such as Google, Baidu, etc.), and the field o...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/27
CPCG06F40/211G06F40/30
Inventor 周忠诚段炼郭建京张圣栋
Owner 湖南星汉数智科技有限公司
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