ADMA2024 Call for Papers
The 20th International Conference on Advanced Data Mining and Applications (ADMA2024) will be held in Sydney, Australia during 3rd ~ 5th December, 2024. It is our great pleasure to invite you to contribute papers and participate in this premier annual event on research and applications of data mining.
ADMA2024 aims at bringing together the experts on data mining from around the world, and providing a leading international forum for the dissemination of original research findings in data mining, spanning applications, algorithms, software and systems, as well as different applied disciplines with potential in data mining. Papers will go through a full peer review process in a double-blind manner. The accepted papers of the conference will be published by Springer in LNAI (Lecture Notes in Artificial Intelligence) and indexed in EI and DBLP. At least one author of an accepted paper must register in full and attend the conference to present the work, otherwise the paper will be removed from the conference proceedings. Excellent accepted papers will be selected and recommended for publication in high-quality journals with the appropriate extension; please see the list of journal special issues for details. This time-honoured conference has been ranked C level by CCF (China Computer Federation).
Submission Site
https://cmt3.research.microsoft.com/ADMA2024
Important Dates
Early Track Submission Deadline | |
Early Track Notification | |
Main Track Submission Deadline | |
Main Track Notification Date | |
Camera-ready Submission Deadline | 15th September, 2024 (AoE) (Sunday) |
Themes and Topics
We invite authors to submit papers relevant to the topics include, but are not limited to:
Data Mining Theories and Technologies
- Data mining foundations and algorithms
- Grand challenges in big data mining
- Mining on data streams
- Graph mining
- Spatial and temporal data mining
- Text, video, multimedia data mining
- Web mining and social networks
- Correlation mining and causality analysis
- Recommender systems
- Generative data mining
- Deep learning models for data mining
- Trustworthy and responsible data mining
- Data mining security and privacy
- Federated and privacy-aware data mining
- Parallel and distributed data mining
- Interactive data mining and visualisation
- Benchmarking and evaluations
- Trends in advanced data mining
Data Mining Applications
- Data mining for edge intelligence
- Data mining for bioinformatics
- Image mining & interpretations
- E-commerce data mining
- Healthcare informatics
- Disaster prediction and prevention
- Data Mining Applications with LLMs
- Financial market analysis
- Software analysis with data mining
- Data mining enhanced education
- Data mining for AgriTech
- Data mining in Internet of Things
- Mining for database management
- Data mining for space science
- Data mining for cyber security
- Data mining for eScience
- Smart Cities applications
- Data mining for societal science
Submission Guidelines
Formatting Guidelines
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The paper should be in English and contain unpublished contributions to the data mining and related fields.
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Manuscripts must be prepared in accordance with the LNAI (Lecture Notes in Artificial Intelligence) format. For the template and details on the LNCS style, see Springer's Author Instructions
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The paper should NOT exceed 15 pages in LNAI format.
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Submissions are reviewed in a double-blind manner. For ADMA2024, the double-blind means that:
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Author identities and affiliations are not disclosed to reviewers during the review process.
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Authors should prepare and submit suitably blinded manuscripts that do not reveal author and affiliation information. Specific requirements to this end are detailed below.
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Authors and reviewers alike make an honest effort to avoid accidentally de-blinding any submission.
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The list of authors at the time of submission is final and cannot be changed.
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"Submitted papers" must comply with all of the rules below. Any violation may result in an "desk reject".
Manuscript Preparation
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Authors must submit PDFs without author names and affiliations. Submitted PDFs must also not contain any metadata that could reveal author identities or affiliations.
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Authors should aim to avoid copy&pasting substantial amounts of text from their own prior publications, as such text blocks may be readily recognized by experts familiar with the state of the art and recent papers in the area.
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Similarly, authors should not directly reuse figures from their own prior publications without attribution. Ideally, “fresh” figures should be prepared and used whenever possible. If that is not a viable option, that is, if a figure must be reused, then a citation should be included giving credit to the original paper from which the illustration has been adapted.
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Authors must refrain from using any specific formatting tricks, linguistic mannerisms, figure styles, or other stylistic idioms that could hint at or disclose the author identity or affiliation.
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Submitted papers should not include an acknowledgements section or funding acknowledgements (even when blinded) since it can indicate the country of residence of (some of) the authors. (Such acknowledgements of course may be added to the camera-ready version.)
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Authors who seek to refer to an online appendix or to supplemental materials (e.g., source code, videos, etc.) may still do so. However, instead of directly providing a URL or tech report number, authors should include a note that the appendices and/or supplemental materials in question are available from the track chair upon request.
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Authors must provide all supplemental materials and/or appendices that a submission refers to in blinded form and sent them to the PC chair by email (or other approaches appointed by the PC chair) before the submission deadline.
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The track chair will retain a copy of all submitted materials for the duration of the reviewing process. Any such provided appendices or supplemental materials are not subject to review and may be consulted by the reviewers at their own discretion.
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It is imperative to acknowledge the contributions of AI models in the generation of textual content. Authors utilizing AI-generated text in their manuscripts are required to assume full responsibility for the accuracy, integrity, and originality of the material presented. Furthermore, any section of the paper employing AI-generated text should include clear documentation and description of the AI system utilized. This transparency ensures that readers can discern between human-authored content and text generated by AI, fostering a culture of accountability and integrity within the scholarly community.
Own Prior Work, Well-Known Projects, and Research Artifacts
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Authors should not upload their manuscript to preprint servers (such as arXiv) or their personal websites while the paper is under review, or otherwise publicly reveal their authorship of the manuscript under review.
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As an exception to the previous rule, if a prior version of the manuscript has already been uploaded to a public preprint server prior to submission (e.g., if the paper is a re-submission of a paper previously rejected at another single-blind conference), then the paper may still be submitted to ADMA2024. However, such papers must be blinded when submitted to ADMA2024.
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In exceptional circumstances that force a violation of the above two rules (e.g., a technical report or thesis must be filed in order for a student to graduate), the authors should contact the Program Chair prior to publicizing their manuscript content to avoid misunderstandings.
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When submitting or extending a prior workshop publication, the workshop paper is treated as an online preprint for the purpose of the double-blind peer-review process. However, authors must proactively disclose the existence of a prior workshop version of a submitted paper. Such information should be emailed to the Program Chair. Failure to disclose a prior workshop publication is considered self-plagiarism.
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After communicating with the Program Chair, submissions with conditions 2., 3., or 4. above are recommended to add a headline (or footer) on the first page with the following information: “This submission is based on Preprints, Paper Announcements, and Prior Workshop Papers. The information has been communicated with the Program Chair. The author(s) and the Program Chair request the reviewers not to actively search for the author names to ensure fairness of the double-blind review process.” Please contact the Program Chair at least 24 hours before the submission deadline if this applies to your submission. If the paper is accepted, the above text should be removed and appropriate citations if any should be added (e.g., citation for prior workshop paper, technical report or thesis and its relation to the accepted paper).
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If your submission is an extended version of a workshop paper with DOI, you will be asked to provide a blinded version of the workshop paper as supplementary material. This will be used by the reviewers to verify that there is sufficient amount of new material in the extended version to warrant a publication at ADMA2024.
Enquiries
General enquiries about paper submissions should be submitted to Program Chairs via emails to adma2024@mq.edu.auProgram Chairs
- Dr. Xuyun (Sean) Zhang, Macquarie University, Australia
- Dr. Wei (Emma) Zhang, The University of Adelaide, Australia
- Prof. Yannis Manolopoulos, Aristotle University of Thessaloniki, Greece