E! 7846 Semantic Analysis for Unrestricted Generalized Employment

SAUGE is an application-oriented collaboration between the Language Technology Group (LTG) at the University of Oslo and two Small- and Medium-Scale Enterprises, one in France (CELI France), the other in Switzerland (4u Group). The project will develop t echnologies that make explicit relevant information encoded in free-form resumes, for example education, skills, or employment history; this information will be represented in an abstract, normalized form that enables reasoning over relevant properties, be it retrieval of personnel by qualification or semi-automated matching demand and supply. These technologies will integrate document layout analysis, syntactic dependency parsing, and concept disambiguation against a domain ontology, i.e. a formal, co mputational model of the employment domain. In the first six-month period of the collaboration, the partners have forged agreement on representation standards and interfaces, as well as initiated a joint, ongoing data collection and annotation effort for all language represented in the consortium.

The market of job offer and job demand traversed in the last times a deep refactoring. On the one hand on-line facilities are absorbing a large share of the job market. On the other hand social media are becoming an excellent channel for recruiting and r esume discovering. These two tendencies are crossed with the fact that the localization of work is becoming less crucial (distance working) and people are more and more willing to change their living place (European Mobility). The potential of this phen omenon is however hampered by lack of technological support: whereas world-level platforms exist for crossing job offer and job demand (e.g. Monster), the matching is still mostly monolingual and constrained by a set of structured data that the user (eith er a job seeker or a job provider) must fill in. Moreover no business effort has been made so far to 'project' the job demand/offer mechanism in the context of the Linked Open Data paradigm. The SAUGE project aims at providing a technology for unrestric ted CV (or resume) parsing able to capture all nuances contained in a manually written CV and to transform them into structured information. The extracted information is then linked in the context of Linked Open Data initiative. The choice of the consor tium has been made in order to maximize the European dimension and collaboration of research-performing SMES with academic partners. The European dimension is necessary in order to cover multiple languages and countries, so as to increase the impact of t he project. Participation of the academic partner is necessary in order to develop novel technologies which are currently unavailable to the involved SMES.