Multi-granularity answer sorting multi-document machine reading understanding method

A reading comprehension, multi-document technology, applied in the field of machine reading comprehension, can solve problems such as poor model representation and generalization ability, inability to integrate multi-granularity question and answer correlation, and limited model input length.
CN110647629AActive Publication Date: 2020-01-03BEIJING INSTITUTE OF TECHNOLOGYGY
5 Cites 36 Cited by

Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
BEIJING INSTITUTE OF TECHNOLOGYGY
Publication Date
2020-01-03

Smart Images

  • Figure 1
    Figure 1
  • Figure 2
    Figure 2
  • Figure 3
    Figure 3
Patent Text Reader

Abstract

The invention discloses a multi-granularity answer sorting multi-document machine reading understanding method, and belongs to the technical field of machine reading understanding application. The method is based on a pre-trained deep learning model. Splitting the document into text fragments through a sliding window, and splicing the text fragments with questions; a plurality of candidate answersgenerated by a plurality of documents are sorted by fusing multi-granularity answer sorting of statistical information, shallow semantic information, deep semantic information and answer ending wordinformation, and the semantic information of different granularities is fully utilized to capture the correlation between a question and the plurality of candidate answers. According to the method, the text representation capability and the generalization capability of a traditional machine reading understanding model are improved by utilizing a pre-trained deep learning model; Meanwhile, the defect that the input length of an existing model for a multi-document scene is limited is overcome, Meanwhile, the answer quality of multi-document machine reading understanding is improved by modeling the correlation between questions and answers from different granularities.
Need to check novelty before this filing date? Find Prior Art

Description

technical field

[0001] The present invention relates to a multi-document machine reading comprehension method for sorting multi-granularity answers, in particular to a multi-document machine reading comprehension method for multi-granularity answer sorting by fusing statistical information, shallow semantic information, deep semantic information and answer ending word information , belonging to the technical field of machine reading comprehension applications. Background technique

[0002] In recent years, the performance of Machine Reading Comprehension (MRC) on multiple machine reading comprehension tasks has been significantly improved, and the machine reading comprehension model based on the attention mechanism is considered to be the most classic in machine reading comprehension. method, it first mathematically models the question and the document, and then fuses the question and document information based on the attention mechanism to form an answer probability model i...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More