Gradually-increased knowledge graph entity extraction method and system for electric power customer service questions and answers

Abstract

The invention discloses a gradually-increased knowledge graph entity extraction method and system for electric power customer service questions and answers, and the method comprises the steps: takingelectric power customer service historical question and answer record data as a basic corpus, and forming a basic data set; extracting named entities and event entities on the basic data set and setting a coexistence relationship between the entities to form an initial seed entity set; extracting named entities and event entities on the corpus data of the electric power customer service field andconstructing a coexistence relationship between the entities to form an entity set corresponding to each data source; screening entities from the entity set corresponding to each power customer service corpus data source to expand the seed entity set, and forming an entity set oriented to the power customer service question and answer knowledge graph. The invention has the capability of autonomously selecting corpus data and entities.

Description

technical field [0001] The invention belongs to the technical field of practical application of intelligent question answering, and relates to an incremental knowledge map entity extraction method and system for electric customer service question answering. Background technique [0002] At present, in the field of practical application of intelligent question answering, the method based on FAQ data sets is mostly used, that is, based on the initial data composed of FAQ pairs, for input questions, retrieve the matching questions in the FAQ data set, and directly The query matches the answer to the question as the answer to the input question. This retrieval method is currently an important technical approach to realize intelligent question answering. However, the retrieval method is very dependent on the initial FAQ data, and its feasibility largely depends on the coverage and accuracy of the collected FAQ data. . [0003] In the field of electric power customer service, th...

AI Technical Summary

Problems solved by technology

However, the business scope of power customer service is wide, involving knowledge from customers to power products, network marketing, etc. Building a complete knowledge map of power customer service is faced with large-scale data collation and high labor costs, and large-scale multi-source heterogeneous data. It is difficult to deal with many problems, and it also faces the problem that large-scale knowledge graphs are not highly targeted to intelligent question answering and the operation efficiency is low.

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