research-article

Entity Personalized Talent Search Models with Tree Interaction Features

Authors:

Cagri Ozcaglar,

Prakhar Sharma,

Alex Shelkovnykov,

Erik BuchananAuthors Info & Claims

WWW '19: The World Wide Web Conference

Pages 3116 - 3122

https://doi.org/10.1145/3308558.3313672

Published: 13 May 2019 Publication History

Abstract

Talent Search systems aim to recommend potential candidates who are a good match to the hiring needs of a recruiter expressed in terms of the recruiter's search query or job posting. Past work in this domain has focused on linear and nonlinear models which lack preference personalization in the user-level due to being trained only with globally collected recruiter activity data. In this paper, we propose an entity-personalized Talent Search model which utilizes a combination of generalized linear mixed (GLMix) models and gradient boosted decision tree (GBDT) models, and provides personalized talent recommendations using nonlinear tree interaction features generated by the GBDT. We also present the offline and online system architecture for the productionization of this hybrid model approach in our Talent Search systems. Finally, we provide offline and online experiment results benchmarking our entity-personalized model with tree interaction features, which demonstrate significant improvements in our precision metrics compared to globally trained non-personalized models.

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Zha RSun YQin CZhang LXu TZhu HChen E(2024)Towards Unified Representation Learning for Career Mobility Analysis with Trajectory HypergraphACM Transactions on Information Systems10.1145/365115842:4(1-28)Online publication date: 6-Mar-2024
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Liu XWang YDong QLu X(2024)Job Title Prediction as a Dual Task of Expertise Prediction in Open Source SoftwareMachine Learning and Knowledge Discovery in Databases. Applied Data Science Track10.1007/978-3-031-70381-2_24(381-396)Online publication date: 22-Aug-2024
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cover image ACM Other conferences

WWW '19: The World Wide Web Conference

May 2019

3620 pages

ISBN:9781450366748

DOI:10.1145/3308558

Editors:
Ling Liu
Georgia Tech, USA
,
Ryen White
Microsoft Research, USA

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 13 May 2019

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WWW '19

WWW '19: The Web Conference

May 13 - 17, 2019

CA, San Francisco, USA

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

Zha RSun YQin CZhang LXu TZhu HChen E(2024)Towards Unified Representation Learning for Career Mobility Analysis with Trajectory HypergraphACM Transactions on Information Systems10.1145/365115842:4(1-28)Online publication date: 6-Mar-2024
https://dl.acm.org/doi/10.1145/3651158
Liu XWang YDong QLu X(2024)Job Title Prediction as a Dual Task of Expertise Prediction in Open Source SoftwareMachine Learning and Knowledge Discovery in Databases. Applied Data Science Track10.1007/978-3-031-70381-2_24(381-396)Online publication date: 22-Aug-2024
https://doi.org/10.1007/978-3-031-70381-2_24
Bied GNathan SPerennes EHoffmann MCaillou PCrépon BGaillac CSebag MElkind E(2023)Toward job recommendation for allProceedings of the Thirty-Second International Joint Conference on Artificial Intelligence10.24963/ijcai.2023/655(5906-5914)Online publication date: 19-Aug-2023
https://dl.acm.org/doi/10.24963/ijcai.2023/655
Lokhande STholia RUpadhyay MChoudhary SRathore KPawar S(2023)Recommendation System for Research Grants2023 7th International Conference On Computing, Communication, Control And Automation (ICCUBEA)10.1109/ICCUBEA58933.2023.10392088(1-4)Online publication date: 18-Aug-2023
https://doi.org/10.1109/ICCUBEA58933.2023.10392088
Brahushi GAhmad U(2022)Empirical Evaluation of Word Representation Methods in the Context of Candidate-Job Recommender Systems2022 9th International Conference on Soft Computing & Machine Intelligence (ISCMI)10.1109/ISCMI56532.2022.10068466(183-187)Online publication date: 26-Nov-2022
https://doi.org/10.1109/ISCMI56532.2022.10068466
Kara ADaniş FKeziban Orman GTurhan S(2022)Extracting Relations Between Sectors2022 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT)10.1109/BDCAT56447.2022.00017(77-82)Online publication date: Dec-2022
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Sun JZhao LLiu ZLi QDeng XWang QJiang Y(2022)Practical differentially private online advertisingComputers and Security10.1016/j.cose.2021.102504112:COnline publication date: 3-Jan-2022
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He MWang TZhu YChen YYao FWang N(2021)FINN: Feature Interaction Neural Network for Person-Job Fit2021 7th International Conference on Big Data and Information Analytics (BigDIA)10.1109/BigDIA53151.2021.9619599(123-130)Online publication date: 29-Oct-2021
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Lin HZhu HWu JZuo YZhu CXiong H(2020)Enhancing Employer Brand Evaluation with Collaborative Topic Regression ModelsACM Transactions on Information Systems10.1145/339273438:4(1-33)Online publication date: 23-May-2020
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