Aspecta: Improving Public Procurement using Natural Language Processing
We collaborate with Aspecta to revolutionize the public procurement process through natural language processing (NLP) and language technologies. The multilabel classification and semantic similarity algorithms, as well as the use of large language models, may enable governments to categorize, group, and analyze procurement data more efficiently.
Public procurement is a vital process that governments undertake to obtain goods and services needed to deliver public services efficiently. However, the procurement process is often tedious and time-consuming, with many challenges faced by both government agencies and suppliers.
The procurement process utilizes software support at many steps. Data-wise adoption of graphical user interfaces of applications and tools can potentially reduce time on task and error rate, if designed correctly. Recommendation, suggestion or validation components can significantly help users to provide consistent and error-prone information. Data provided will be of higher quality.KInIT teamed up with Aspecta to help them pursue their goal of supporting digital transformation. We will research efficient methods for automated text classification in procurement requests. We will carry out a set of experiments that will result in a report on suitability of multiple approaches to multilabel classification. We will explore linguistic and statistical ones, including incorporation of large language models, such as SlovakBERT, that are both popular and well performing on many NLP tasks. Based on the results, adaption of the existing software application for procurement requests may significantly improve in efficiency.
Transforming theory into practice always brings interesting results and space for new opportunities. And when we combine the NPL and digital transformation, it is valid multiple times.
Delivery manager, Aspecta
Research Engineer 03/2022 – 09/2023
Lead and Researcher