With more and more applications of machine learning and data mining methods to real-world problems, the necessity of understanding why those methods lead to certain results has also become more and more obvious.

The reasons for this need to understand are diverse: users might need to understand because money is on the line — as investment or profit — or even lives, e.g. in healthcare or disaster preparedness. Or they might want to understand because computational methods can then act as hypothesis generators: observing the results of a pattern mining operation or a produced clustering triggers new insights and informs new research directions - the final step in the “knowledge discovery” process.

There are also legal frameworks that require interpretability and explainability of algorithmic decisions, e.g. the EU General Data Protection Regulation or the US Fair Credit Reporting Act. In machine learning (ML), most of the focus has been on using symbolic representations of non-symbolic models to help with explainability: “Why does the model give certain predictions?”.

Data mining, specifically pattern mining and clustering, is already largely symbolic but lacks the label-provided supervision that can be leveraged in ML. As such, there are two questions one needs to answer to understand data mining results: 1) “How did the algorithm arrive at the result?”, and 2) “What does this result mean w.r.t. the underlying data?” I.e., instead of explaining a result, one needs to understand a process and/or interpret a result.

The best way of answering these questions come from offering supervision in the form of involving the user by making data mining interactive. This involvement gives the user a better understanding of how successive mining steps build on each other, helping with interpreting the final result, explaining how the process arrived at it, and therefore building trust. Venues for publishing work on understanding ML have been proliferated under the “explainable AI” (XAI) label whereas this remains an underexplored topic for data mining. After the end of the “Interactive Data Exploration and Analytics” (IDEA) workshop series at KDD (2013–2017),
opportunities for presenting on-going research have been rare. We therefore intend to bring the topic back to ECML PKDD, host of the 2012 “Instant Interactive Data Mining” workshop, to take the temperature of the community on that topic, assemble work on progress on it, and in general bring interested researchers together for exchange and discussion.

The workshop will take place virtually on September 23, 2022.

*Submissions*

We will solicit submissions including but not limited to the following topics:
• Interactive pattern mining and clustering
• Human-in-the-loop data mining systems
• Result visualization
• Data mining feedback options
• User preference and constraint learning
• Subjective interestingness measures
• Use cases of interactive, explainable and interpretable data mining
• Result sampling techniques

The following types of papers can be submitted:

- Long papers will be 9 pages of content and an unlimited number of references in the Springer LNCS style and should report on novel, unpublished work that might not be quite mature enough for a conference or journal submission.
- Extended abstracts will be 2 pages in Springer LNCS style and summarize recent publications fitting the workshops.
- Demo papers will be 5 pages in Springer LNCS and describe a concrete implementation of an interactive mining system.

Papers are to be submitted in pdf format at https://easychair.org/conferences/?conf=idm22

Each paper will be reviewed by at least two members of the Program Committee on the basis of technical quality, relevance, significance, and clarity. Submitting a paper to the workshop means that if the paper is accepted at least one author should present the paper at the workshop. Long papers and extended abstract will be presented orally while demo papers will be demoed.

*Key dates*

Paper Submission Monday, June 20, 2022
Author notification Wednesday, July 13, 2022
Camera-ready Wednesday, July 27, 2022
Workshop Friday, September 23, 2022

*Contacts*

David Auber david.auber@u-bordeaux.fr
Christel Vrain christel.Vrain@univ-orleans.fr
Ronan Bureau ronan.bureau@unicaen.fr
Albrecht Zimmermann albrecht.zimmermann@unicaen.fr

Workshop website: https://involvd.greyc.fr/?page_id=83