Li, Jindong
Xing, Qianli
Wang, Qi
Chang, Yi
Chapter History
First Online: 17 September 2023
Ethical Statement
: The following statement outlines the ethical considerations that were taken into account during the research process.<b>Data Collection.</b> In the experimental part, we used a publicly available dataset. And the public dataset has preprocessed the information involved in the data, so there are no issues of confidentiality and privacy.<b>Protection of Participants.</b> Throughout the research process, there were no additional participants except the authors. The personal information of all personnel is not related to the experiment. The experiment only used information from public dataset.<b>Data Analysis.</b> Our data analysis is only from the perspective of algorithmic metrics, without any discrimination or illegal tendencies.<b>Conflict of Interest.</b> We declare that they have no conflicts of interest that may have influenced the research.<b>Research Involving Animals.</b> This study does not involve the use of animals.<b>Cultural Sensitivity.</b> The research team was aware of the potential cultural biases that could have an impact on the study results. To ensure cultural sensitivity, the research team worked with participants from diverse cultural backgrounds and used culturally appropriate language in the consent form and data collection procedures.<b>Beneficence.</b> The research team considered the potential benefits and harms of the study. The research team made efforts to minimize any potential harms to participants while maximizing the potential benefits to both individuals and society.
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.