Knowledge graph question-answering system for professional field

A professional field and knowledge map technology, applied in the field of natural language processing, can solve problems such as not being able to better meet the multi-source heterogeneous data question answering needs, and achieve the effect of eliminating potential semantic differences and enriching data forms

Active Publication Date: 2021-08-06
NO 54 INST OF CHINA ELECTRONICS SCI & TECH GRP
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Problems solved by technology

At present, the question answering technology based on knowledge graph can be roughly divided into the method based on semantic analysis and the meth

Method used

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  • Knowledge graph question-answering system for professional field
  • Knowledge graph question-answering system for professional field
  • Knowledge graph question-answering system for professional field

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Embodiment Construction

[0030] In order to make the above objects, features and advantages of the present invention more comprehensible, the present invention will be further described in detail below through specific embodiments and accompanying drawings.

[0031] A knowledge graph question answering system oriented to the professional field of the present invention adopts an overall architecture such as figure 1 As shown, it includes a knowledge extraction module and an answer generation module; this embodiment uses data in the aerospace field as an example for illustration.

[0032] The knowledge extraction module is used to use the idea of ​​knowledge transfer, use the text mode to cooperate with the image and video modes to extract multi-modal knowledge from aerospace data, and build a knowledge map in the aerospace field;

[0033] The answer generation module is used to base the externally input aerospace questions on the aerospace domain knowledge map, adopt the analysis method and semantic ma...

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Abstract

The invention discloses a knowledge graph question-answering system for the professional field. The system comprises a knowledge extraction module and an answer generation module, the processing process mainly comprises the following steps of extracting cross-modal collaborative professional field knowledge: performing knowledge extraction by utilizing text modal collaborative image and video modal data so as to solve the problem that a traditional knowledge extraction method is difficult to be directly applied to a professional field due to multi-source isomerism and multi-modality; questions and answers of multi-source knowledge are fused, and multi-source candidate answers are obtained through semantic matching and answer generation by utilizing professional domain knowledge information; and semantic fusion of the multi-source candidate answers, and generation of a final answer based on answer confidence reordering and answer key point reorganization of the multi-source knowledge. The knowledge graph question-answering system for the professional field solves the knowledge question-answering of multi-source heterogeneous and multi-modal data in the professional field, and is suitable for the multi-modal knowledge question-answering in other fields.

Description

technical field [0001] The invention relates to a knowledge graph question answering system for professional fields, which belongs to the technical field of natural language processing. Background technique [0002] With the development of computer and Internet technology, the data for professional fields is increasing exponentially. These data are large in scale and have the characteristics of multi-source heterogeneity. On the one hand, the data in professional fields come from different data sources, such as literature and reports. On the other hand, data in the professional field has obvious heterogeneous characteristics, covering text, picture, video and other modalities. How to quickly and accurately obtain the information needed by users from these multi-source heterogeneous professional field data has become an urgent problem to be solved, and the most important technology to solve this problem is intelligent question answering technology based on knowledge graph. ...

Claims

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Application Information

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IPC IPC(8): G06F16/332G06F16/36G06F40/35
CPCG06F16/3329G06F16/367G06F40/35
Inventor 裴新宇楚博策郭琦刘敬一高晓倩韩长兴王梅瑞耿虎军陈金勇高峰
Owner NO 54 INST OF CHINA ELECTRONICS SCI & TECH GRP
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