Document language models, query models, and risk minimization for information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Relevance based language models
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Relevance and ranking in online dating systems
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
PROSPECT: a system for screening candidates for recruitment
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
A field relevance model for structured document retrieval
ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
Using social data for resume job matching
Proceedings of the 2012 workshop on Data-driven user behavioral modelling and mining from social media
MEET: a generalized framework for reciprocal recommender systems
Proceedings of the 21st ACM international conference on Information and knowledge management
Efficient multifaceted screening of job applicants
Proceedings of the 16th International Conference on Extending Database Technology
iHR: an online recruiting system for Xiamen Talent Service Center
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
International Journal of Metadata, Semantics and Ontologies
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We investigate the difficult problem of matching semi-structured resumes and jobs in a large scale real-world collection. We compare standard approaches to Structured Relevance Models (SRM), an extensionof relevance-based language model for modeling and retrieving semi-structured documents. Preliminary experiments show that the SRM approach achieved promising performance and performed better than typical unstructured relevance models.