Poison-target literature knowledge mining method and system based on network crawling

Abstract

The invention provides a poison-target literature knowledge mining method and system based on network crawling. The poison-target literature knowledge mining method comprises the steps of: acquiring poison and target data information, and processing the poison and target data information, so as to establish a comprehensive data set; developing a web crawler tool; crawling poison and target literature text information by utilizing the web crawler tool based on the comprehensive data set, and processing the poison and target literature text information to establish a literature text database; based on the literature text database, determining a poison-target potential action relationship by utilizing a natural language processing technology to form a poison-target relationship knowledge base; and performing poison-target literature knowledge mining by utilizing the literature text database and the poison-target relationship knowledge base. The poison-target literature knowledge mining method and the system based on network crawling are high in efficiency, good in accuracy and high in intelligent degree.

Description

technical field [0001] The invention relates to the technical field of the Internet, in particular to a poison-target document knowledge mining method and system based on web crawling. Background technique [0002] With the rapid development of toxicology and molecular biology and other disciplines, a large number of data sets related to poisons and targets have emerged on the Internet, but at present, the resource storage of these data sets is scattered, the format is heterogeneous, and different poisons and target data sets exist. With a large amount of redundant information, poison names and aliases are confused, and there is a lack of unified naming conventions. Although the emergence of these data sets provides a reference for the vast number of toxicology researchers, due to the lack of uniform data standards, the lack of necessary data filtering and quality control mechanisms, resulting in low efficiency of manual retrieval and query, too much redundant information an...

AI Technical Summary

Problems solved by technology

[0003] The existing literature retrieval system for poisons and targets is based on keywords input by users, such as poison names, target names, or a combination of both, to perform information retrieval and fuzzy matching in the background literature database, and find documents with high similarity and return them to users. The search method still stays at the level of static content search and matching, it is difficult to obtain the hidden knowledge in the literature, and it is even more difficult to carry out knowledge mining from the massive biomedical literature, which seriously affects the work efficiency of poison research and scientific research workers

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