THE CLASSIFICATION OF OCCUPATIONS FOR ONLINE JOB ADVERTISEMENTS CHALLENGE - The second round of the European Statistics Awards for Web Intelligence
Online job advertisements contain various types of information including a job description, information about the company looking to hire, job benefits, requirements for job seekers, etc. In order to calculate meaningful statistics given the data collection method and size of the online job advertisements datasets, occupational class labels must be provided for these various entries. Within the WI CLASSIFICATION CHALLENGE, teams will compete using advanced modelling techniques to develop an efficient and robust automated solution for correctly assigning class labels.
The second round of European Statistics Awards for Web Intelligence will begin in June 2024 with registrations open until 15 July 2024.
Timeline
The competition will begin on 1 June 2024 and will run for four months until 30 September 2024. The deadline for registration is 15 July 2024.
Awards
Accuracy Award
First Prize EUR 10 000
Second Prize EUR 5 000
Third Prize EUR 3 000
Reusability Award
First Prize EUR 10 000
Second Prize EUR 5 000
Third Prize EUR 3 000
Innovativity Award
First Prize EUR 5 000
Second Prize EUR 3 000
Third Prize EUR 1 000
Teams
Teams comprising a maximum of five individuals with diverse backgrounds and expertise in programming and web intelligence are eligible to participate in the competition. This contest presents an exceptional chance to apply your understanding of classification modelling in an actual context and potentially receive up to EUR 10 000 for developing the most accurate model. If your team secures the top spot for all three awards, you could earn up to EUR 25 000 in this round.
The Web Intelligence - Deduplication Challenge
The winners of the web intelligence - deduplication challenge have been announced
A part of the European Statistics Awards Program aims at stimulating innovation in the area of Web Intelligence for European statistics, focusing on identifying potential duplicate job postings on websites as a basic condition to produce high quality statistics from online job advertisements.