The aim of this master thesis is to examine how Semantic Web technology can be used in the field of Human Resource Management, more specifically how it can be used to improve areas of online job recruitment, focusing on improving searching, and examining how to match CVs and job ads to find the person best fit for the job.
Today's job search engines are usually based on word matching between the search keywords and the vacancy contents. The results returned are thus often too broad, or has nothing to do with what the searcher was looking for. Introducing Semantic Web technology, organising all competencies in a CV and competency requirements in a vacancy into an ontology, this could be used as a basis of search and comparison that gives much better accuracy than word matching.
In order to gain knowledge about the field and various systems successfully using Semantic Web technologies, a small test system was created. This system is based around a small ontology consisting of a competency branch, a job category branch and other branches with enough features to apply logical reasoning to and ask queries about. The ontology was developed in Protégé, with queries being asked in SPARQL. All is tied together with Jena, an open source Java toolkit, running locally on a Tomcat server. CVs and job ads consists of competencies and competency requirements respectively, and queries and comparison of these competencies are conducted using the ontology relations instead of matching words.
A survey of the technologies used to achieve this will be discussed, as well as some alternatives and competing technologies.