Text visualization corresponds to the visual representation of the contents of text documents with the aim to summarize, understand, and explore the textual content. With the recent boom in digital literature and increasing number of users on the social media platforms, enormous amount of text data is freely available to be analyzed. The huge size of such data warrants the usage of automatic techniques to extract and communicate useful information. To this end, along with text mining and natural language processing (NLP) techniques, visualization has played an important role in enhancing the understandability of this data. To date, numerous visualization techniques have been devised to help in providing a quick visual overview of a large amount of text data from various perspectives. The topics offered within the scope of this seminar look into state-of-the-art visualization techniques and visual analytics systems that help in understanding diverse types of text data ranging from static text documents to dynamic conversations.
- Lehrende(r): Shivam Agarwal
- Lehrende(r): Shahid Latif
Vorlesung | |
Dozenten | Prof. Dr. Volker Gruhn Prof. Dr. Fabian Beck |
Termine | Mo. 10:15-11:45 Uhr |
Mi. 18:15-19:45 Uhr | |
Ort | SH 601 |
- Lehrende(r): Shivam Agarwal
- Lehrende(r): Fabian Beck
- Lehrende(r): Irene Eusgeld
- Lehrende(r): Stefan Gries
- Lehrende(r): Wilhelm Koop
- Lehrende(r): Shahid Latif
- Lehrende(r): Frederik Ahlemann
- Lehrende(r): Helge Alsdorf
- Lehrende(r): Ruben Franz
- Lehrende(r): Marvin Jagals
- Lehrende(r): Erik Karger
- Lehrende(r): Anna Yuliarti Khodijah
- Lehrende(r): Alexandar Schkolski
- Lehrende(r): Christopher Ziolkowski
- Lehrende(r): Frederik Ahlemann
- Lehrende(r): Anna Yuliarti Khodijah
- Lehrende(r): Asvina Ramachandra