基于双层级联文本分类的简历信息抽取

本文提出了一种基于双层级联文本分类的方法,用于简历信息的自动抽取。本方法将简历文本分解为文本块和文本串,并将简历中包含的信息分解为概要信息与详细信息。首先对简历文本中的文本块进行切分与分类,抽取出概要信息,然后选择可能包含详细信息的文本块,将其切分为文本串,再通过对文本串的分类抽取出详细信息。对1200份中文简历的实验结果表明,本方法适用于简历信息的自动抽取和管理。

Resume Information Extraction Based on Cascaded Double- layer Classification

This paper presents an approach based on cascaded double-layer text classification for resume information extraction.This approach first divides a resume into block and string.Then it divides the target information into general information and detailed information.It first extracts general information by block segmentation and classification.Then it selects those blocks that may contain predefined detailed information with a fuzzy strategy.At last,it segments these blocks into strings and labels the strings with detailed information classes.The experimental results on 1200 Chinese resumes show that our approach is suitable for the information extraction and management of resumes.