Method and equipment for constructing intelligent question-answering system through question generation data set

Abstract

The invention discloses a method and equipment for constructing an intelligent question-answering system through a question generation data set. The method comprises the following steps: constructinga tourism domain knowledge graph; performing question analysis on natural language questions proposed by a user, performing word segmentation and word vector training on the questions, and in a word segmentation process, using a jaeba tool and adding a tourism domain dictionary set in advance; performing entity extraction on the natural language questions by using a Bert-BiLSTM+CRF model; matchingthe extracted entities with entities in a knowledge graph; if a matched entity exists in the knowledge graph, selecting the entity; if no matched entity exists in the knowledge graph, performing semantic similarity calculation, and selecting the closest entity; matching the selected entities and attributes with triples in a knowledge graph; and returning the corresponding attribute value as an answer to the question to be provided for the user. The invention also provides a device for realizing the method, a terminal and a readable storage medium. According to the invention, the information required by the user can be returned conveniently and accurately.

Description

technical field [0001] The invention belongs to the field of information query and retrieval, and in particular relates to a method and equipment for constructing an intelligent question answering system through question generation data sets, and is especially suitable for information search of knowledge graphs in the field of tourism. Background technique [0002] Since the concept of knowledge graph was proposed in 2012, major Internet companies have built the next generation of intelligent search engines based on it, such as Google Knowledge Graph, Sogou Zhicube, etc., hoping to create a new information retrieval and provide new ideas for solving information retrieval problems. At the same time, the domain knowledge graph has also developed rapidly in recent years. Compared with the traditional knowledge graph, the advantage of the domain knowledge graph is that the data is more concentrated, it is more convenient to process, and the ambiguity between entities is greatly ...

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