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First Online: 18 September 2023

Ethic Statement

: In this ethical statement, we will discuss the ethical implications of our work in relation to machine learning and data mining. We recognize the importance of ethics in all aspects of our work and are committed to upholding ethical principles in our research and its application. In this statement, we will outline the potential ethical issues that arise from our work and the steps we have taken to mitigate these issues.

: The datasets of our work are all public datasets. We have obtained all necessary permissions and have followed best practices for data download, processing, and storage to ensure that the privacy of individuals is protected.

: Our work does not involve the inference of personal information from data.

: Our work may have potential applications in policing contexts. We are aware of the potential ethical implications of this and are committed to ensuring that our work is not used in ways that violate human rights or result in harm to individuals. We will carefully consider the potential uses of our work and will take appropriate steps to prevent its misuse.

Conference Information

Conference Acronym: ECML PKDD

Conference Name: Joint European Conference on Machine Learning and Knowledge Discovery in Databases

Conference City: Turin

Conference Country: Italy

Conference Year: 2023

Conference Start Date: 18 September 2023

Conference End Date: 22 September 2023

Conference Number: 23

Conference ID: ecml2023

Conference URL: https://2023.ecmlpkdd.org/

Peer Review Information (provided by the conference organizers)

Type: Double-blind

Conference Management System: CMT

Number of Submissions Sent for Review: 829

Number of Full Papers Accepted: 196

Number of Short Papers Accepted: 0

Acceptance Rate of Full Papers: 24% - The value is computed by the equation "Number of Full Papers Accepted / Number of Submissions Sent for Review * 100" and then rounded to a whole number.

Average Number of Reviews per Paper: 3.63

Average Number of Papers per Reviewer: 4.5

External Reviewers Involved: Yes

Additional Info on Review Process: Applied Data Science Track: 239 submissions, 58 accepted papers; Demo Track: 31 submissions, 16 accepted papers.