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Deep text matching method and device based on sorting learning

A sorting learning and matching method technology, which is applied in the direction of text database query, unstructured text data retrieval, special data processing applications, etc., can solve the problems of not being able to judge which sentence is more similar and affect the model matching effect, and achieve accurate text matching The effect of high rate, enhanced generalization ability, and faster fitting speed

Active Publication Date: 2019-07-16
ZHONGKE DINGFU BEIJING TECH DEV
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Problems solved by technology

However, in the above method of using sentence pairs, for multiple sentences that are relatively similar to the training sentences, the model cannot judge which sentence is more similar, which in turn affects the final matching effect of the model

Method used

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  • Deep text matching method and device based on sorting learning
  • Deep text matching method and device based on sorting learning
  • Deep text matching method and device based on sorting learning

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Embodiment Construction

[0056] Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numerals in different drawings refer to the same or similar elements unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the present invention. Rather, they are merely examples of apparatuses and methods consistent with aspects of the invention as recited in the appended claims.

[0057] In view of the fact that the existing deep matching models mostly use sentence pair matching, and there is a problem of inaccurate matching similarity, this embodiment provides a deep text matching method based on ranking learning to be applied in the deep matching model, wherein the method is applicable to in various depth matching models.

[0058] figure 1 It is a schematic flowchart ...

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Abstract

The invention provides a deep text matching method and device based on sorting learning, and the method specifically comprises the steps: firstly, obtaining sentence pairs composed of assumed sentences and reasoning sentences, the reasoning sentences comprising positive reasoning sentences and a plurality of negative reasoning sentences, and the assumed sentences being related to semantics of thepositive reasoning sentences and not related to semantics of the negative reasoning sentences; secondly, carrying out corresponding processing on sentences in the sentence pairs, forming sentence vectors, calculating loss values of a preset loss function according to matching degree values among the sentence vectors, and adjusting parameters of a depth matching model according to the loss values;and finally, carrying out text matching on the input statement by utilizing the finally obtained depth matching model through parameter adjustment. The input sentence pairs are expanded into the sentence sequences from the two sentence pairs and comprise the positive example type data and the negative example type data, due to the fact that the input number and types of the model are expanded, thefitting speed of the model is increased, and the matching precision of the model can be improved.

Description

technical field [0001] The present application relates to the technical field of natural language processing, in particular to a deep text matching method and device based on ranking learning. Background technique [0002] Text matching is an important basic problem in natural language processing, and many tasks in natural language processing can be abstracted as text matching tasks. For example, webpage search can be abstracted as a correlation matching problem between webpage and user search query, automatic question answering can be abstracted as a matching problem between candidate answers and questions, and text deduplication can be abstracted as a text-to-text similarity matching problem. [0003] Traditional text matching techniques (such as the vector space model algorithm in information retrieval) mainly solve the matching problem at the vocabulary level. In fact, the matching algorithm based on lexical coincidence has great limitations and cannot solve many proble...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/33G06F17/27
CPCG06F16/33G06F40/289G06F40/30
Inventor 李健铨刘小康刘子博晋耀红
Owner ZHONGKE DINGFU BEIJING TECH DEV
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