Using semantic-based AI to reduce the editorial board’s workload at The Finnish Population Register Centre (VRK)
Semantic-based AI case study of the Finnish Population Register Centre (VRK):
The Finnish Population Register Centre (VRK) promotes digitalisation in Finland. The uninterrupted and smooth operation of the public entities and NGOs that fall under the organisation’s responsibility is vital for the functioning of Finnish society. Along with other duties, VRK runs and continuously develops Suomi.fi, a website that provides information about public services for citizens and businesses in Finland.
The public sector agency handles tens of thousands of documents in a free text format coming from thousands of different channels. Extracting, summarising and classifying information from natural text is a critical topic to help save workload and improve service quality. Digital Workforce developed a semantic-based AI solution for VRK that can automatically pick out contextually similar documents. The identified documents are used to create a single topical summary document, which is then scanned to eliminate reiteration, redundancy, and out-of-topic sentences.
In this case study, you will learn:
- How AI has helped VRK to organise and classify service description documents?
- How a semantic-based AI solution can automatically pick out contextually similar documents from service descriptions?
- How an AI-developed template can help improve the quality of content and free up people’s time from quality control to more productive work?