Department of Information Systems
Poznań University of Economics and Business
The scientific article of our Department’s employees entitled “Sentence Embeddings and Semantic Entity Extraction for Identification of Topics of Short Fact-Checked Claims” has been published in open access. The paper describes an approach to assigning topics to claims verified by fact-checking agencies.
The inaugural meeting of the Student Research Group “Data Science” in the academic year 2024/2025 was held at the Poznań University of Economics and Business. During the meeting, the planned activities of the SRG Data Science and proposals for areas of activity in the coming months were discussed. Additionally, employees of our Department presented the opportunities and challenges related to data analysis in various areas.
On October 4, 2024, a meeting of the staff of the Department of Information Systems at the Poznań University of Economics and Business took place. The meeting was led by Prof. Krzysztof Węcel, the new head of the Department, who was appointed to this position on October 1, 2024. The meeting was dedicated to presenting and discussing the Department’s strategy for the upcoming academic year in connection with the new … Read More
During the 28th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2024), Dr. Włodzimierz Lewoniewski presented a paper entitled “Exploring the Challenges and Potential of Generative AI: Insights from an Empirical Study” and a paper entitled “Supporting fact-checking process with IT tools”. The conference was held on September 11-13, 2024 in hybrid mode.
On September 9-12, 2024, scientists from the Department of Information Systems presented their works at the CLEF 2024 conference, which took place in Grenoble (France). This was the 25th edition of the CLEF (Conference and Labs of the Evaluation Forum), a key event in the field of information and language technologies, focusing on the evaluation of information systems. Thanks to a variety of test tasks, participants can compare and improve … Read More
An article by our scientists entitled “OpenFact at CheckThat! 2024: Combining Multiple Attack Methods for Effective Adversarial Text Generation” has been published in open access. The paper describes the approach that won first place in an international competition in the area of information credibility.
During the international conference Wikimania 2024, a panel discussion entitled “Keynote: Opening the Academia” took place, in which Dr. Włodzimierz Lewoniewski participated. The panel concerned the topic of open science and its various aspects. In particular, the challenges faced by academic institutions that try to implement the principles of open science and the obstacles that hinder these processes were discussed. The role of Wikimedia projects, such as Wikipedia, in the … Read More
The work of our scientists on the analysis of digital currency exchanges has been published on the Springer website. As part of the research, models for predicting the success and bankruptcy of cryptocurrency exchanges were developed, based on financial data and information collected from open Internet sources such as Wikipedia and Wikidata. The aim of the work was to identify key aspects that can support the risk analysis process and … Read More
During the Wikimania 2024 conference, the results of scientific research on measuring Americanization in various regions of the world based on open data from Wikipedia and Wikidata were presented. The conducted research reveals differences in interest in American topics depending on the level of development of countries, offering a new perspective on global cultural dominance. At the same time, the analysis emphasizes the role of Wikipedia and Wikidata as tools … Read More
A team of scientists from the Department of Information Systems at the Poznań University of Economics and Business took part in the “CheckThat! 2024” organized as part of the international conference CLEF (Conference and Labs of the Evaluation Forum). The goal was to verify the robustness of popular text classification approaches used for credibility assessment problems.