Event portrait-oriented text analysis method for dialogue system

Abstract

The invention provides an event portrait-oriented text analysis method for a dialogue system. The event portrait-oriented text analysis method comprises the following steps of: 1, extracting an event relationship; 2, event extraction and structuring; 3, event similarity calculation and fusion; 4, event trigger word extraction and argument extraction. According to the method, the method for constructing the event graph is fully researched, the logic structure relation between events is described by adopting a knowledge graph structure, and meanwhile, in order to describe the events more clearly, the multi-dimensional attributes of the events are portrayed. The invention provides a system structure constructed by a affair graph. The structure comprises text corpus collection, event relation extraction template construction, event extraction and structuring, event similarity calculation and fusion, event trigger word extraction and argument extraction model construction, event relation pair construction and graph database storage. In addition, by utilizing the system structure, a sequential affair map, a causal affair map, a conditional affair map, a turning affair map and a concurrent affair map are constructed.

Description

technical field [0001] The invention relates to an event portrait-oriented text analysis method for a dialogue system. Background technique [0002] Event is one of the core concepts of human society, and people's social activities are often driven by events. The evolution rules and patterns of events occurring successively in time and space are very valuable knowledge. However, the existing typical knowledge graphs focus on entities and their attributes and relationships, and lack the description of the important human knowledge of logic. In order to make up for this deficiency, the event graph came into being, which can reveal the evolution law and development logic of events, and describe and record human behaviors. The event graph describes knowledge in a logical society. Nodes represent events, and edges between nodes represent logical relationships. In essence, the event graph is a knowledge base for event logic. [0003] Human memory of the world is formed by the c...

AI Technical Summary

Problems solved by technology

For dialogue systems, it is difficult for the existing dialogue systems to deeply understand the contextual causality of the dialogue, and the system can only give smarter responses based on different contexts if it understands common sense knowledge, such as "take a taxi first" before "going to the airport".

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