This IO covers development of methods for extracting job-related information from websites. The goal of tasks in the frame of this IO is to analyze the content of job postings, other job-related textual data and information about job seekers, to detect topics within them and to feed into the JKB. This has multiple applications: (1) Grouping similar job openings (2) Finding duplicate job openings (3) Automatically generating a hierarchical categorization of jobs (4) Matching job seeker skills to job openings. In addition, this IO aimed at extending multiple visualization methods for the various prediction results and search tasks developed throughout the project. We used methods from information retrieval and recommender systems to evaluate how to present search results, post-retrieval clustering and computed taxonomies to the user. Based on user tests, we measured the usefulness of the systems, and thus be able to compare the various algorithms with each other. This IO benefited from the studies done in IO1 and IO2 i.e. Modeling and Meta-Modeling of Job Knowledge for Labour Market and Identification and Analysis of the in the European labour market Data respectively.