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From:
Toine Bogers <[log in to unmask]>
Reply To:
Toine Bogers <[log in to unmask]>
Date:
Wed, 29 Jun 2022 11:40:24 +0000
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************************************************
FINAL CALL FOR PAPERS

2nd Workshop on Recommender Systems for Human Resources (RecSys in HR 2022)
Organized at the 16th ACM Conference on Recommender Systems, to be held in Seattle, WA, USA, September 18-23, 2022.

Website: https://recsyshr.aau.dk/
Contact: [log in to unmask]<mailto:[log in to unmask]>
************************************************


***Scope***
The field of Human Resources is on the forefront of adopting AI technologies, according to PWC over 40% of HR-functions of international companies use AI-applications. This so-called HR Technology (HR Tech) aims to replace or support Human Resource functions such as talent acquisition and management, employee compensation, workforce analytics, and performance management.

Recommender Systems, broadly defined as systems that aim to support users in decision making by suggesting and offering relevant content, play an integral role in the rapid rise of HR Tech. Their applications range from assisting the talent acquisition process through matching, screening, filtering, and assessing candidates, to broader tasks such as user modeling from diverse sources like resumes, (video) interviews, of (psychometric) assessments and tests.

The focus of the RecSys in HR workshop series is on all areas of HR: recruitment (or job recommendation), retention, training and development, performance and career management, and talent pool management, and compensation and benefits. We invite submissions of original research on all aspects of recommender systems or related techniques—such as search, descriptive and predictive analytics, and interactive visualizations—applied to any of these key HR areas. In addition, we welcome position papers that discuss and present novel ideas or insights concerning approaches, key challenges, or theoretical or methodological issues that have the potential to inspire substantive discussion and lead to significant advances in the field.

Relevant topics include (but are not limited to):

  *   Theoretical and practical contributions on the application of recommender systems and related algorithms to the field of HR
  *   Interfaces for HR analytics tools that employ recommender systems & AI and their role in decision making
  *   Bias, fairness, ethics of the use of recommender systems & AI in HR
  *   Multi-stakeholder analyses of recommender systems in HR
  *   Explainability of recommender systems for HR tasks
  *   HR metrics and analytics relevant to the evaluation of recommender systems in HR processes
  *   Economic & societal consequences of recommender systems & AI in HR
  *   Novel approaches to recommendation in HR
  *   User studies
  *   Data sets for recommendation and HR Tech
  *   Cold-start scenarios in recommendation for HR
  *   Case studies of real-world implementations
  *   People analytics
  *   Expert recommendation & profiling
  *   User representation and modeling
  *   Human-augmented decision-making in HR
  *   Automatic extraction and classification of job functions and skills


***Submissions***
Authors are invited to submit papers of 4-10 pages on any of the relevant workshop topics in one of these categories:

  *   Research papers that either describe mature work, including evaluation.
  *   Position papers that discuss and present novel ideas or insights concerning approaches, key challenges, or theoretical or methodological issues.

All submissions should be in English and should not have been published or currently under review for publication elsewhere. Papers should be formatted in the CEUR workshop proceedings template (https://www.overleaf.com/latex/templates/template-for-submissions-to-ceur-workshop-proceedings-ceur-ws-dot-org/wqyfdgftmcfw).

All the papers submitted will be reviewed using a double-blind refereeing process by at least two members of the program committee. Submissions can be made through the EasyChair submission system: https://easychair.org/conferences/?conf=recsyshr2022

Papers will be published in the CEUR Workshop proceedings series.


***Workshop format***
We aim to make the RecSys in HR workshop an inclusive, interactive, and inspiring event. In order to make the workshop as interactive as possible, we plan for long Q&A sessions after each presentation and after a planned panel on relevant challenges for HR tech to allow for more discussion. In addition, we hope to increase interactivity by closing the workshop with a break-out session where the attendees discuss some of the most relevant issues and challenges that have come up during the day. To help us organize and seed these break-out sessions, we plan on sending a short survey to confirmed workshop attendees in the weeks leading up to RecSys. We plan to use this survey to collect information not only about what the attendees see as the most pressing challenges and interesting topics in HR analytics, but also to help us profile our audience through questions about their affiliation (industry, academia, government), their specialization (HR, computer science).

The workshop will be organized as a full day event. In addition to the activities outlined above, two keynote speakers from industry, government or academia will be invited.


***Important dates***
Paper submission deadline: August 5, 2022
Notification of paper acceptance: August 27, 2022
Camera-ready version deadline: September 10, 2022
Workshop (at RecSys 2022): September 18-23, 2022


***Organizers***
Toine Bogers – Aalborg University Copenhagen, Denmark
David Graus – Randstad Groep Nederland, the Netherlands
Francisco Gutiérrez – KU Leuven, Belgium
Chris Johnson – Indeed, US
Mesut Kaya – Aalborg University Copenhagen, Denmark
Sepideh Mesbah – Randstad Groep Nederland, the Netherlands


***Venue***
The workshop will be in conjunction with the 16th ACM Conference on Recommender Systems, to be held in Seattle, WA, USA, September 18-23, 2022. Similar to the main conference, the workshop will most likely take place in a hybrid format, allowing for both physical and online attendance.




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