Workshop on Text Mining and Generation (TMG) @ ICCBR 2023
- July 17, 2023
- Co-located with ICCBR 2023
- Aberdeen, Scotland
Digital text data is produced across different sources such as social media. Simultaneously, very often only structured data is available. Within CBR, cases of the former are usually handled by using methods of Textual CBR, while Process-Oriented CBR addresses on the latter type of data. By leveraging their generic research origins, i.e., text mining and text generation approaches, we aim to diminish this gap. The target of text mining is to extract (useful) structured information from unstructured text. In contrast, text generation attempts to (automatically) create text from structured information or distributed knowledge. The goal of the TMG workshop is to bring these two perspectives together by eliciting research paper submissions that aim for applying text mining and generation approach in the context of CBR. We welcome any submission from any domain aiming to contribute to to close this gap.
|May 10, 2023||Paper submission|
|June 12, 2023||Paper notification|
|June 26, 2023||Camera-ready copy|
|July 17, 2023||Workshop date|
Call for Papers
We welcome any submissions that deal with transforming the representation of data between structured and unstructured formats in the context of CBR-based systems: (applied) research papers, theoretical papers, user studies or prospective papers. Topics include, but are not limited to, the following:
- Text mining for argumentation.
- Case-based knowledge representation of text.
- Similarity-based retrieval and ranking.
- Informed similarity measures for structured text.
- Generating descriptions for graph-based argument case representations.
- Generating case-based explanations for retrieval.
- Methods for Explainable CBR.
- Ethical aspects of AI for text generation (e.g., mitigating bias or misinformation).
- Integration of background knowledge and machine learning.
- CBR and knowledge graphs.
- Graph-to-text generation with knowledge graphs.
- Knowledge graph refinement, particularly featuring text-based signals.
- Snippet generation for search results.
- CBR for Deep Learning with Text.
The submission of the papers should be in accordance to the CEUR-WS style and have to be submitted via EasyChair. The workshop is running a single-blind review process. Authors can submit the following types of papers:
- Full Paper (10–16 pages, including references)
- Short Paper (5–9 pages, including references)
Tentiative Workshop Schedule
|11:30||13:00||Currently pending: Invited talk with discussion|
|14:00||15:30||Session 2 with panel discussion|
|16:00||17:30||Poster session and socializing|
University of Liverpool