2017 – Topics of interest

We solicit research works that are broadly related to data science on employment data, including data cleaning, data normalization, classification, clustering, and ranking. Specific topics of interest include (but are not limited to):

  • Machine learning for resume and job parsing
  • Data standardization, classification and normalization for Human Capital Management
  • Ontology mining for human capital knowledge graph construction
  • Large-scale information extraction and inference for HCM
  • Entity resolution and deduplication for HCM (e.g., people and job aggregators)
  • Reputation systems for worker rankings and expertise
  • Data mining for career pathing
  • Semantic job matching
  • Semantic search for recruitment
  • Recommender systems for e-recruiting
  • Labor market analytics for economic and workforce development (e.g., measuring skills gaps)
  • Labor market economics (e.g., impact of policy and regulation on hiring)