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Resume information extraction with cascaded hybrid model

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Ming ZhouAuthors Info & Claims

ACL '05: Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics

Pages 499 - 506

https://doi.org/10.3115/1219840.1219902

Published: 25 June 2005 Publication History

Abstract

This paper presents an effective approach for resume information extraction to support automatic resume management and routing. A cascaded information extraction (IE) framework is designed. In the first pass, a resume is segmented into a consecutive blocks attached with labels indicating the information types. Then in the second pass, the detailed information, such as Name and Address, are identified in certain blocks (e.g. blocks labelled with Personal Information), instead of searching globally in the entire resume. The most appropriate model is selected through experiments for each IE task in different passes. The experimental results show that this cascaded hybrid model achieves better F-score than flat models that do not apply the hierarchical structure of resumes. It also shows that applying different IE models in different passes according to the contextual structure is effective.

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Cited By

Juárez JSantos CBrizuela C(2021)A Comprehensive Review and a Taxonomy Proposal of Team Formation ProblemsACM Computing Surveys10.1145/346539954:7(1-33)Online publication date: 18-Jul-2021
https://dl.acm.org/doi/10.1145/3465399
Tobing BSuhendra IHalim C(2019)Catapa Resume ParserProceedings of the 2019 3rd International Conference on Natural Language Processing and Information Retrieval10.1145/3342827.3342832(68-74)Online publication date: 28-Jun-2019
https://dl.acm.org/doi/10.1145/3342827.3342832
Sandanayake TLimesha GMadhumali TMihirani WPeiris M(2018)Automated CV Analyzing and Ranking Tool to Select Candidates for Job PositionsProceedings of the 6th International Conference on Information Technology: IoT and Smart City10.1145/3301551.3301579(13-18)Online publication date: 29-Dec-2018
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ACL '05: Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics

June 2005

657 pages

General Chair:
Kevin Knight
University of Southern California

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Association for Computational Linguistics

United States

Publication History

Published: 25 June 2005

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ACL '05 Paper Acceptance Rate 77 of 423 submissions, 18%;

Overall Acceptance Rate 85 of 443 submissions, 19%

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Cited By

Juárez JSantos CBrizuela C(2021)A Comprehensive Review and a Taxonomy Proposal of Team Formation ProblemsACM Computing Surveys10.1145/346539954:7(1-33)Online publication date: 18-Jul-2021
https://dl.acm.org/doi/10.1145/3465399
Tobing BSuhendra IHalim C(2019)Catapa Resume ParserProceedings of the 2019 3rd International Conference on Natural Language Processing and Information Retrieval10.1145/3342827.3342832(68-74)Online publication date: 28-Jun-2019
https://dl.acm.org/doi/10.1145/3342827.3342832
Sandanayake TLimesha GMadhumali TMihirani WPeiris M(2018)Automated CV Analyzing and Ranking Tool to Select Candidates for Job PositionsProceedings of the 6th International Conference on Information Technology: IoT and Smart City10.1145/3301551.3301579(13-18)Online publication date: 29-Dec-2018
https://dl.acm.org/doi/10.1145/3301551.3301579
Gu XYang HTang JZhang JSubrahmanian VRokne JKumar RCaverlee JTong H(2016)Web user profiling using data redundancyProceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining10.5555/3192424.3192491(358-365)Online publication date: 18-Aug-2016
https://dl.acm.org/doi/10.5555/3192424.3192491
Guo SAlamudun FHammond T(2016)RésuMatcherExpert Systems with Applications: An International Journal10.1016/j.eswa.2016.04.01360:C(169-182)Online publication date: 30-Oct-2016
https://dl.acm.org/doi/10.1016/j.eswa.2016.04.013
Hong WLi LLi TPan WGrossman RUthurusamy RDhillon IKoren Y(2013)iHRProceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining10.1145/2487575.2488199(1177-1185)Online publication date: 11-Aug-2013
https://dl.acm.org/doi/10.1145/2487575.2488199
Huang RRiloff EDaelemans W(2012)Bootstrapped training of event extraction classifiersProceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics10.5555/2380816.2380853(286-295)Online publication date: 23-Apr-2012
https://dl.acm.org/doi/10.5555/2380816.2380853
Sainani AReddy PMaheshwari S(2012)Mining special features to improve the performance of e-commerce product selection and resume processingInternational Journal of Computational Science and Engineering10.1504/IJCSE.2012.0461837:1(82-95)Online publication date: 1-Mar-2012
https://dl.acm.org/doi/10.1504/IJCSE.2012.046183
Çelik DElçi A(2012)An ontology-based information extraction approach for résumésProceedings of the 2012 international conference on Pervasive Computing and the Networked World10.1007/978-3-642-37015-1_14(165-179)Online publication date: 28-Nov-2012
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Yu JZhao HLiu F(2012)User real-time interest prediction based on collaborative filtering and interactive computing for academic recommendationProceedings of the 8th international conference on Intelligent Computing Theories and Applications10.1007/978-3-642-31576-3_16(119-127)Online publication date: 25-Jul-2012
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