PHOAKS: a system for sharing recommendations
Communications of the ACM
GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
A Framework for Collaborative, Content-Based and Demographic Filtering
Artificial Intelligence Review - Special issue on data mining on the Internet
Learning Collaborative Information Filters
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
ICCBR '99 Proceedings of the Third International Conference on Case-Based Reasoning and Development
METIOREW: An Objective Oriented Content Based and Collaborative Recommending System
Revised Papers from the nternational Workshops OHS-7, SC-3, and AH-3 on Hypermedia: Openness, Structural Awareness, and Adaptivity
Job Offer Management: How Improve the Ranking of Candidates
ISMIS '09 Proceedings of the 18th International Symposium on Foundations of Intelligent Systems
Collaborative filtering based on an iterative prediction method to alleviate the sparsity problem
Proceedings of the 11th International Conference on Information Integration and Web-based Applications & Services
ITWP'03 Proceedings of the 2003 international conference on Intelligent Techniques for Web Personalization
A hybrid approach to managing job offers and candidates
Information Processing and Management: an International Journal
Proceedings of the 13th International Conference on Computer Systems and Technologies
A recommender system for job seeking and recruiting website
Proceedings of the 22nd international conference on World Wide Web companion
iHR: an online recruiting system for Xiamen Talent Service Center
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
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Online recruitment services suffer from shortcomings due to traditional search techniques. Most users fail to construct queries that provide an adequate and accurate description of their (job) requirements, leading to imprecise search results. We investigate one potential solution that combines implicit profiling methods and automated collaborative filtering (ACF) techniques to build personalised query-less job recommendations. Two ACF strategies are implemented and evaluated in the JobFinder domain.