A Conversational Approach to Process-Oriented Case-Based Reasoning

Abstract

Process-oriented case-based reasoning (POCBR) supports workflow modeling by retrieving and adapting workflows that have proved useful in the past. Current approaches typically require users to specify detailed queries, which can be a demanding task. Conversational case-based reasoning (CCBR) particularly addresses this problem by proposing methods that incrementally elicit the relevant features of the target problem in an interactive dialog. However, no CCBR approaches exist that are applicable for workflow cases that go beyond attribute-value representations such as labeled graphs. This paper closes this gap and presents a conversational POCBR approach (C-POCBR) in which questions related to structural properties of the workflow cases are generated automatically. An evaluation with cooking workflows indicates that C-POCBR can reduce the communication effort for users during retrieval.

Cite

Text

Zeyen et al. "A Conversational Approach to Process-Oriented Case-Based Reasoning." International Joint Conference on Artificial Intelligence, 2018. doi:10.24963/IJCAI.2018/762

Markdown

[Zeyen et al. "A Conversational Approach to Process-Oriented Case-Based Reasoning." International Joint Conference on Artificial Intelligence, 2018.](https://mlanthology.org/ijcai/2018/zeyen2018ijcai-conversational/) doi:10.24963/IJCAI.2018/762

BibTeX

@inproceedings{zeyen2018ijcai-conversational,
  title     = {{A Conversational Approach to Process-Oriented Case-Based Reasoning}},
  author    = {Zeyen, Christian and Müller, Gilbert and Bergmann, Ralph},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2018},
  pages     = {5404-5408},
  doi       = {10.24963/IJCAI.2018/762},
  url       = {https://mlanthology.org/ijcai/2018/zeyen2018ijcai-conversational/}
}