Geological ontology-based geological report text information extraction method

Abstract

The invention provides a geological ontology-based geological report text information extraction method, which comprises the steps of S1, performing preprocessing operation on a geological report document, converting a file type into a data source format, and performing sentence segmentation, word segmentation, stop word removal and part-of-speech tagging; S2, constructing a place name dictionarylibrary and a geological entity dictionary library by utilizing the structured information, expanding on the basis of the existing geological domain ontology, and forming a place name ontology and a geological time ontology; and S3, extracting geological entity information, space-time relationship information and attribute information from the geological report text through a mode matching methodand a rule matching method. The method has the advantages that a large number of training data sets do not need to be marked manually, and manpower and material resources are saved; an existing information extraction model is abstracted and improved, and a certain thought is provided for information extraction in other fields.

Description

technical field [0001] The invention relates to the field of geological information retrieval, in particular to a geological report text information extraction method based on geological ontology. Background technique [0002] For a long time, through a series of geological survey projects and geological data collection and submission mechanism, the geological survey field has accumulated a large amount of geological survey data, and gradually formed a system of various geological professional databases and geological "content" composed of unstructured data. Library". As a typical representative of big data, geological big data is mainly composed of two parts. One is the structured space with normalized definitions and well-structured in various professional databases that have been formed in the existing geological field. Data sets, this type of data usually has a predefined schema for storage and retrieval; the other type is an unstructured text data set composed of texts...

AI Technical Summary

Problems solved by technology

Structured data is usually stored and managed using relational or spatial databases, but the nature of unstructured data makes them difficult to manage through virtual applications

There are many types of unstructured data and scattered information, and the information is often richer than structured data and has greater potential value. Using traditional file systems to manage these data will reduce the efficiency of answering queries and retrieving statistical information, increasing Difficulty in retrieving and mining data

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