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Deep text matching method and device based on unlogged word processing

A technology of unregistered words and registered words, which is applied in electronic digital data processing, text database query, special data processing applications, etc., can solve problems such as model matching effect interference, and achieve the effect of avoiding interference.

Pending Publication Date: 2019-07-09
ZHONGKE DINGFU BEIJING TECH DEV
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Problems solved by technology

[0006] This application provides a deep text matching method and device based on unregistered word processing based on a matching sequence to solve the problem of unregistered words interfering with the model matching effect

Method used

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  • Deep text matching method and device based on unlogged word processing
  • Deep text matching method and device based on unlogged word processing
  • Deep text matching method and device based on unlogged word processing

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Embodiment Construction

[0085] 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.

[0086] Aiming at the problem that existing deep matching models generally process unregistered words into null or random values, which affects the final matching effect of the model, this embodiment provides a deep text matching method based on unregistered word processing, which is applied in Among the deep matching models, the method can be applied to various deep matching models.

[0087] f...

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Abstract

The invention provides a deep text matching method and device based on unregistered word processing. When the depth matching model is trained, word segmentation is carried out on input sentences in aword vector auxiliary word vector mode. Words obtained through word segmentation of all the sentences are continuously subjected to word segmentation processing and expressed through word vectors, andthen a result of connection of the word vectors and the word vectors serves as the sentence quantity of the input sentences. Alternatively, the input statements are represented by initial word vectors, similarity weighting processing is performed on the initial word vectors, weighted word vectors are generated. Word segmentation processing is performed on the statements. The statements are represented by word vectors, and then the result of connection between the word vectors and the word vectors is used as the statement vector representation of the input statements. Due to the fact that newcharacters which do not appear in the training set rarely occur, interference of unlogged-in words on the model matching effect can be avoided to a certain extent in the mode that the characters and the word vectors are combined, and text 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 unregistered word processing. 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...

Claims

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Application Information

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IPC IPC(8): G06F17/27G06F16/33
CPCG06F40/289Y02D10/00
Inventor 李健铨刘小康刘子博晋耀红
Owner ZHONGKE DINGFU BEIJING TECH DEV
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