RELATION EXTRACTION SYSTEM AND METHOD ADAPTED TO FINANCIAL ENTITIES AND FUSED WITH PRIOR KNOWLEDGE

The present invention relates to a relation extraction system adapted to financial entities and fused with prior knowledge and a method thereof, the system at least comprising: a deep pretraining module, for training and generating a deep pretrained model for recognizing attributes of the financial...

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Bibliographic Details
Main Authors CAO, Nan, JIN, Hai, ZHANG, Teng, SHI, Xuanhua, WAN, Yao, LI, Mengfan
Format Patent
LanguageEnglish
Published 14.03.2024
Subjects
CALCULATING
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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Summary:The present invention relates to a relation extraction system adapted to financial entities and fused with prior knowledge and a method thereof, the system at least comprising: a deep pretraining module, for training and generating a deep pretrained model for recognizing attributes of the financial entities; a keyword analyzing module, for extracting and outputting positional information and importance vectors of keywords in a Chinese finance-related text; an attention mechanism module, for encoding the positional information of the keywords to obtain attention masks, and inputting them with entity information into the deep pretrained model to acquire text feature vectors; and an optimal margin distribution model module, for predicting financial-entity relations based on the text feature vectors and the importance vectors. Aiming at low applicability of existing models to specific Chinese fields, the present invention obtains more accurate extraction results of entities and related features in Chinese finance-related texts.
Bibliography:Application Number: US202318217207