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Inf. Syst."],"published-print":{"date-parts":[[2020,10,31]]},"abstract":"<jats:p>Employer Brand Evaluation (EBE) is to understand an employer\u2019s unique characteristics to identify competitive edges. Traditional approaches rely heavily on employers\u2019 financial information, including financial reports and filings submitted to the Securities and Exchange Commission (SEC), which may not be readily available for private companies. Fortunately, online recruitment services provide a variety of employers\u2019 information from their employees\u2019 online ratings and comments, which enables EBE from an employee\u2019s perspective. To this end, in this article, we propose a method named Company Profiling\u2013based Collaborative Topic Regression (CPCTR) to collaboratively model both textual (i.e., reviews) and numerical information (i.e., salaries and ratings) for learning latent structural patterns of employer brands. With identified patterns, we can effectively conduct both qualitative opinion analysis and quantitative salary benchmarking. Moreover, a Gaussian processes--based extension, GPCTR, is proposed to capture the complex correlation among heterogeneous information. Extensive experiments are conducted on three real-world datasets to validate the effectiveness and generalizability of our methods in real-life applications. The results clearly show that our methods outperform state-of-the-art baselines and enable a comprehensive understanding of EBE.<\/jats:p>","DOI":"10.1145\/3392734","type":"journal-article","created":{"date-parts":[[2020,5,25]],"date-time":"2020-05-25T22:43:36Z","timestamp":1590446616000},"page":"1-33","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":13,"title":["Enhancing Employer Brand Evaluation with Collaborative Topic Regression Models"],"prefix":"10.1145","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1921-3036","authenticated-orcid":false,"given":"Hao","family":"Lin","sequence":"first","affiliation":[{"name":"School of Economics and Management, Beihang University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hengshu","family":"Zhu","sequence":"additional","affiliation":[{"name":"Talent Intelligence Center, Baidu Inc., Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junjie","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Economics and Management, Beihang University, China and Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuan","family":"Zuo","sequence":"additional","affiliation":[{"name":"School of Economics and Management, Beihang University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chen","family":"Zhu","sequence":"additional","affiliation":[{"name":"Talent Intelligence Center, Baidu Inc., Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Xiong","sequence":"additional","affiliation":[{"name":"Management Science and Information Systems Department, Rutgers University, Newark, NJ, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2020,5,23]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1177\/097226290901300304"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1108\/13620430410550754"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1080\/02650487.2005.11072912"},{"key":"e_1_2_1_4_1","volume-title":"Nonlinear Programming","author":"Bertsekas D. 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