ADMA2026 Call for Research Papers

The 22nd International Conference on Advanced Data Mining and Applications (ADMA2026) will be held in Hong Kong SAR, China, November 1-3, 2026. 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.

ADMA2026 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, such as smart transportation, fintech, intelligent manufacturing, biomedical science, green computing, personalized education, etc. Papers will go through a full peer review process in a double-blind manner. Accepted papers will be published by Springer in LNAI (Lecture Notes in Artificial Intelligence) and indexed in EI and DBLP. This time-honoured conference has been ranked C level by CCF (China Computer Federation).

Submission Site

https://cmt3.research.microsoft.com/ADMA2026

Important Dates (AoE Time)

  Submission Deadline
May 29, 2026

   Notification
August 3, 2026

  Camera-Ready Submission Deadline
August 17, 2026

  Conference Dates
November 1-3, 2026

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

  • The paper should be in English and contain unpublished contributions to data mining and related fields.

  • 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

  • The paper should NOT exceed 15 pages in LNAI format.

  • Submissions are reviewed in a double-blind manner. i.e.

    • Author identities and affiliations are not disclosed to reviewers during the review process.

    • Authors should prepare and submit suitably blinded manuscripts that do not reveal author and affiliation information. Specific requirements are detailed below.

    • Authors and reviewers alike make an honest effort to avoid accidentally de-blinding any submission.

  • The list of authors at the time of submission is final and cannot be changed.

  • Submitted papers must comply with all of the rules below. Any violation may result in a "desk reject".

Manuscript Preparation

  • Authors must submit PDFs without author names and affiliations. Submitted PDFs must also delete any metadata that could reveal author identities or affiliations.

  • 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.

  • 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.

  • 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.

  • 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.)

  • 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.

Supplementary Materials

  • Supplementary materials, such as technical appendices, source codes, and datasets, may be submitted separately in a single file to CMT, in ZIP or PDF format within 20MB, using the "Upload Supplementary Material" button.

  • To comply with the double-blind submission policy, please do NOT reveal any author identity or affiliation information in your supplementary materials, especially for the readme file of your source codes.

  • There is no page limit for your supplementary materials. The main paper, including references, acknowledgements, limitation claims, etc., should NOT exceed 15 pages in the LNAI format. Please do not attach technical appendices at the end of the main paper if this causes your file to be over the 15-page limit. Any submission violating this submission policy will be desk-rejected.

  • The deadline for supplementary materials submission will be 3 days after the paper submission deadline.

  • Instead of using CMT, you may also choose to upload your supplementary materials to an anonymous repository (e.g., Anonymous GitHub) and provide a URL in your paper. So, our reviewers can refer to the repository for your supplementary materials. This option is recommended if your files are over the 20MB size limit. Please do not edit the repository after the supplementary materials submission deadline.

Dual Submission Policy

  • Submissions to ADMA2026 must not be under review or accepted for publication in any other archival venue at the time of submission. Archival venues include conferences, journals, or workshops with official proceedings. Dual submissions to such venues are strictly prohibited and will result in desk rejection.

  • Submissions that are also being considered for non-archival workshops (e.g., workshops without published proceedings or with only informal abstracts) are permitted, provided that the authors clearly disclose this information to the Program Chair at the time of submission. The non-archival workshop must not require exclusive submission rights.

  • Authors uncertain about whether a venue qualifies as archival should contact the Program Chair in advance of submission.

Own Prior Work, Well-Known Projects, and Research Artifacts

  • 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.

  • 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 ADMA2026. However, such papers must be blinded when submitted to ADMA2026.

  • 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.

  • 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.

  • 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).

  • 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 ADMA2026.

Conflicts of Interest

We use CMT’s conflict management system, through which authors should flag conflicts with members of the Program Committee. X and Y have a conflict of interest if any of the following applies:

  • X and Y have worked in the same university or company in the past two years, or will be doing so in the next six months on account of an accepted job offer. Different campuses within the same university system do not count as the same university for this purpose - UC Berkeley does not have a conflict with UC Santa Barbara.
  • X has been a co-author of a paper with Y in the last three years.
  • X has been a collaborator within the past two years, as evidenced in a joint publication (subsumed by the stricter rule on co-authorship above), joint research project, or co-organizing events (e.g., co-chairs of conferences), or are collaborating now (including co-authorship on papers not resulted in final publication yet).
  • X is the master’s/PhD thesis advisor of Y or vice versa, irrespective of how long ago this was.
  • X is a relative or close personal friend of Y.

It is the full responsibility of all authors of a paper to identify and declare all COIs with members of the Program Committee (reviewers, meta-reviewers, and PC chairs) prior to the submission deadline. Submissions with undeclared conflicts or spurious conflicts will be desk-rejected.

CMT Acknowledgment

The Microsoft CMT service was used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support.

Contact Program Chairs

  • Wen Hua (The Hong Kong Polytechnic University, Hong Kong, China): wency.hua@polyu.edu.hk
  • Quanming Yao (Tsinghua University): qyaoaa@tsinghua.edu.cn
  • Hongzhi Yin (The University of Queensland, Australia): h.yin1@uq.edu.au