E-recruitment is one of the most successful e-business applications supporting both, headhunters and job seekers. The explosive growth of online job offers makes the usage of information extraction techniques to build up, e.g., job portals in a semi-automatic way a necessity. Existing approaches, however, hardly cope with the heterogeneous and semi-structured nature of job offers nor do they consider potentials offered by Web 2.0 technologies. This paper proposes an information extraction system called “JobOlize” 1 , realized for arbitrarily structured IT job offers. To improve extraction quality, a hybrid approach is employed, combining existing NLP-techniques with a new form of context-driven extraction, incorporating layout, structure and content information. To allow users a proper adaptation of the extraction results while preserving the look and feel of the original Web pages, a rich client interface is provided. The improvements in extraction quality are justified on basis of a case study and the experiences gained are generalized and critically reflected by discussing lessons learned.
['Christina Buttinger', 'Birgit Pröll', 'Jürgen Palkoska', 'Werner Retschitzegger', 'Manfred Schauer', 'Reinhold Immler']
JobOlize Headhunting by Information Extraction in the Era of Web 2.0