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Data Science Group
The group focuses on various topics in Natural Language Processing and Information Retrieval areas, working mainly with text content. One of the long-lasting themes are research topics in which we pay special attention to temporal aspects of text and temporal document collections such as collections of news articles (e.g., both document timestamps and various temporal expressions embedded in text).
In particular, the following research projects have been carried recently:
- Open domain question answering in large news article collections
- Multi-hop question answering and generation
- Timeline generation from news article datasets
- Multiple timeline generation
- Comparative timeline generation
- Information retrieval and access approaches to news archives
- Event time detection
- Named entity retrieval
- Bias detection in text
- Text readability estimation
- Temporal Natural Language Inference (TNLI)
- Automatic humor generation
- Legal AI (e.g., dialogue generation)
- Text summarization
- Temporal text collection summarization
- Multi-modal document summarization
The group collaborates actively with researchers from: Kyoto University (JP), AIST (JP), Kyoto Sangyo University (JP), University of La Rochelle (FR), Alibaba Group (CN), Nankai University (CN), Karlsruhe Institute of Technology (DE), University of Tsukuba (JP), University of Normandy (FR), Polytechnic Institute of Tomar (PT), University of Porto (PT), IIT Patna (IN), University of Gothenburg (SE), Nanyang Technological University (SG), Takushoku University (JP), Sorbonne University (FR), Polish-Japanese Academy of Information Technology (PL), Universiti Utara Malaysia (MY), Cork Institute of Technology (IE), Fraunhofer Austria (AT) and TuWien (AT).
The Data Science Lab gratefully acknowledges generous grants by Daniel Swarovski Corporation AG, Innio Jenbacher GmbH & Co OG, Innsbrucker Kommunalbetriebe AG (IKB), TINETZ-Tiroler Netze GmbH and Vereinigung der Österreichischen Industrie, Landesgruppe Tirol (Industriellenvereinigung Tirol), which fund the endowed professorship from 2021 to 2026.