Information retrieval method and system based on multi-hop knowledge reasoning

Abstract

The invention discloses an information retrieval method and system based on multi-hop knowledge reasoning. According to the method, a knowledge graph is constructed through information in a retrieval library, and a retrieval result is reasoned by utilizing the knowledge graph in an information retrieval process. The problem that data information in a retrieval library cannot be fully mined by a traditional information retrieval method is solved by means of a knowledge graph. By means of multi-hop knowledge reasoning, the property of prediction basis can be provided, information in an existing retrieval library is used for reasoning a result, and meanwhile the basis and source of the retrieval result can be provided for a user. The system designed for the method comprises a retrieval library information processing module, an information retrieval module, a knowledge graph learning module and an interactive interface. According to the method and the system, the information in the retrieval library is more fully retrieved, the retrieval content is reliable, and a retrieval basis is provided.

Description

technical field [0001] The invention relates to the technical field of information retrieval, in particular to an information retrieval method and system based on multi-hop knowledge reasoning. Background technique [0002] Information Retrieval (Information Retrieval, IR) is a process of finding relevant information in the retrieval database according to the user's specific needs. With the advent of the era of big data, the scale of data continues to increase, and the types of data have become more diverse. How to perform accurate and efficient retrieval in massive data is an important issue. Traditional information retrieval methods, such as: Boolean logic retrieval, proximity retrieval, phrase retrieval, word truncation retrieval, field restriction retrieval, etc., are only simple matching, and have not fully explored the correlation between data in the context of big data. [0003] The Knowledge Graph is a structured way to describe concepts, entities and their relatio...

AI Technical Summary

Problems solved by technology

[0005] In the context of big data, the amount of information in the retrieval database is also rapidly expanding, but the existing information retrieval methods do not use these data to build a knowledge map, so they cannot use the information in the retrieval database for reasoning and prediction

In this way, the information in the retrieval database cannot be fully utilized, and under some retrieval conditions, the retrieval results will become insufficient and unreliable

Images