PAKDD 2025 : 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining

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<span property="v:description"> PAKDD 2025 : 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining</span> </span> </h2> <h3> <span id="share-buttons"> <a href="http://www.facebook.com/sharer.php?u=http://wikicfp.com/cfp/servlet/event.showcfp?eventid=182187" target="_blank"><img src="/cfp/images/share/facebook.png" alt="Facebook"/></a><a href="http://twitter.com/share?url=http://wikicfp.com/cfp/servlet/event.showcfp?eventid=182187&text=PAKDD 2025 : 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining" target="_blank"><img src="/cfp/images/share/twitter.png" alt="Twitter" /></a><a href="http://www.linkedin.com/shareArticle?mini=true&url=http://wikicfp.com/cfp/servlet/event.showcfp?eventid=182187" target="_blank"><img src="/cfp/images/share/linkedin.png" alt="LinkedIn" /></a><a href="https://plus.google.com/share?url=http://wikicfp.com/cfp/servlet/event.showcfp?eventid=182187" target="_blank"><img src="/cfp/images/share/google.png" alt="Google" /></a></span> </h3> <br>Conference Series : <a href='/cfp/program?id=2299&s=PAKDD&f=Pacific-Asia Conference on Knowledge Discovery and Data Mining'>Pacific-Asia Conference on Knowledge Discovery and Data Mining</a><br>  </td></tr> <tr><td align="center" > Link: <a href="https://pakdd2025.org/" target="_newtab">https://pakdd2025.org/</a> </td></tr> <tr><td> </td></tr> <tr><td> <table cellpadding="0" cellspacing="5" align="center"> <tr valign="middle"> <td align="center"> <table cellpadding="0" cellspacing="0" align="center"> <tr valign="middle"><td align="center"> <table class="gglu" cellpadding="3" cellspacing="1" align="center"> <tr bgcolor="#e6e6e6"> <th>When</th> <td align="center"> Jun 10, 2025 - Jun 13, 2025 </td> </tr><tr bgcolor="#f6f6f6"> <th>Where</th> <td align="center">Sydney, Australia</td> </tr> <tr bgcolor="#e6e6e6"> <th>Submission Deadline</th> <td align="center"> <span xmlns:v="http://rdf.data-vocabulary.org/#" typeof="v:Event"> <span property="v:summary" content="Submission Deadline"></span> <span resource="http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=182187" rel="v:url"></span> <span property="v:startDate" content="2024-11-30T00:00:00">Nov 30, 2024</span> </span> </td> </tr> <tr bgcolor="#f6f6f6"> <th>Notification Due</th> <td align="center"> <span xmlns:v="http://rdf.data-vocabulary.org/#" typeof="v:Event"> <span property="v:summary" content="Notification Due"></span> <span resource="http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=182187" rel="v:url"></span> <span property="v:startDate" content="2025-01-25T00:00:00">Jan 25, 2025</span> </span> </td> </tr> <tr bgcolor="#e6e6e6"> <th>Final Version Due</th> <td align="center"> <span xmlns:v="http://rdf.data-vocabulary.org/#" typeof="v:Event"> <span property="v:summary" content="Final Version Due"></span> <span resource="http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=182187" rel="v:url"></span> <span property="v:startDate" content="2025-02-15T00:00:00">Feb 15, 2025</span> </span> </td> </tr> </table> </td></tr> <tr><td align="center" > <table class="gglu" cellpadding="3" cellspacing="1" align="center"> <tr><td></td></tr> <tr bgcolor="#f6f6f6"> <td align="center"> <h5><a class="blackbold" href="/cfp/allcat"><b>Categories</b></a>    <a href="../call?conference=data mining">data mining</a>   <a href="../call?conference=data science">data science</a>   <a href="../call?conference=big data">big data</a>   <a href="../call?conference=applications of data science">applications of data science</a></h5> </td></tr> </table> </td></tr> </table> </td> </tr> </table> </td></tr> <tr><td> </td></tr> <tr><td align="center" > <div xmlns:dc="http://purl.org/dc/elements/1.1/"> <span property="dc:title" content="PAKDD 2025"></span> <span property="dc:description" content="29th Pacific-Asia Conference on Knowledge Discovery and Data Mining"></span> <span property="dc:identifier" content="http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=182187"></span> <span property="dc:source" content="https://pakdd2025.org/"></span> <span property="dc:publisher" content="WikiCFP"></span> </div> <h3>Call For Papers</h3> </td></tr> <tr><td align="center" > <div class="cfp" align="left"> The 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) will take place in Sydney, Australia, on June 10-13, 2025. PAKDD 2025 is soliciting contributed technical papers for presentation at the Conference and publication in the Conference Proceedings by Springer. In particular, we solicit novel, high-quality, and original research papers that provide innovative insights into all facets of knowledge discovery and data science, including but not limited to theoretical foundations of mining, inference, and learning, big data technologies, as well as security, privacy, and integrity. We also encourage visionary papers on emerging topics and application-based papers offering innovative technical advancements to interdisciplinary research and applications of data science. <br> <br>Important Dates <br> Paper Submission Deadline November 30, 2024 <br> Paper Acceptance Notification January 25, 2025 <br> Camera Ready Papers Due February 15, 2025 <br> <br>Conference Topics <br> <br>Topics of relevance for the conference include, but are not limited to, the following: <br>Theoretical Foundations <br> Generative AI, quantum ML, neuro-symbolic methods and reasoning, causal reasoning, non-IID learning, OOD generalization, representation learning, optimization methods <br> Model explainability, XAI <br> <br>Learning Methods and Algorithms <br> Clustering, classification, pattern mining and association rules discovery <br> Supervised learning, semi-supervised learning, few-shot and zero-shot learning, active learning <br> Reinforcement learning and bandits <br> Transfer learning, federated learning <br> Anomaly detection, outlier detection <br> Learning in recommendation engines <br> Learning in streams and in time series <br> Learning on structured data, images, texts and multi-modal data <br> Online learning, model adaption <br> Graph mining and GraphNNs <br> <br>Data processing for learning <br> Dimensionality reduction, feature extraction, subspace construction <br> Data cleaning and preparation, data integration and summarization <br> Learning in real-time <br> Big data technologies <br> Information retrieval <br> Data/entity/event/relationship extraction <br> User interfaces and visual analytics <br> <br>Security, Privacy, Ethics, Information Integrity and Social Issues <br> Modeling credibility, trustworthiness, and reliability <br> Privacy-preserving data mining and privacy models <br> Model transparency, interpretability, and fairness <br> Misinformation detection, monitoring, and prevention <br> Social issues, such as health inequities, social development, and poverty <br> <br>Interdisciplinary Research on Data Science Applications <br> Social network/media analysis and dynamics, reputation, influence, trust, opinion mining, sentiment analysis, link prediction, and community detection <br> Symbiotic human-AI interaction, human-agent collaboration, and socially interactive robots <br> Internet of Things, logistics management, network traffic and log analysis, and supply chain management <br> Business and financial data, computational advertising, customer relationship management, intrusion and fraud detection, and intelligent assistants <br> Medical and public health applications, drug discovery, healthcare management, and epidemic monitoring and prevention <br> Methods for detecting and combating spamming, trolling, aggression, toxic online behaviors, bullying, hate speech, and low-quality and offensive content <br> Climate, ecological, and environmental science, and resilience and sustainability <br> Astronomy and astrophysics, genomics and bioinformatics, high energy physics, robotics, AI-assisted programming, and scientific data <br> <br>Submission Details <br>https://pakdd2025.org/authors-kit <br> <br>If you have any questions, please feel free to contact us at pakdd2025.pc@gmail.com <br> </div> </td></tr> </table> </center> </div> <div class="contsec"> <center><h3> Related Resources </h3></center> <div class="cfp" align="left"> <table cellpadding="0" cellspacing="0px" align="center" width="100%"> <tr valign="top"> <td> <table cellpadding="4" cellspacing="3" align="center" width="100%"> <tr><td> <a href="/cfp/servlet/event.showcfp?eventid=127474">IEEE-Ei/Scopus-ITCC 2025</a>   2025 5th International Conference on Information Technology and Cloud Computing (ITCC 2025)-EI Compendex </td></tr> <tr><td> <a href="/cfp/servlet/event.showcfp?eventid=127472">SPIE-Ei/Scopus-DMNLP 2025</a>   2025 2nd International Conference on Data Mining and Natural Language Processing (DMNLP 2025)-EI 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Intelligence (BDAI 2025) </td></tr> <tr><td> <a href="/cfp/servlet/event.showcfp?eventid=177942">COIT 2025</a>   5th International Conference on Computing and Information Technology </td></tr> <tr><td> <a href="/cfp/servlet/event.showcfp?eventid=181673">Hong Kong-MIST 2025</a>   2025 Asia-Pacific Conference on Marine Intelligent Systems and Technologies (MIST 2025) </td></tr> </table> </td> </tr> </table> </div> </center> </div> <DIV class="footer"> <center> <table cellpadding="0" cellspacing="0" width="100%"><tr valign="top"> <td align="left"> <table cellpadding="0"> <tr><td align="left"> <a href="/cfp/about.jsp">About Us</a> | <a href="mailto:wikicfp@gmail.com">Contact Us</a> | <a href="/cfp/data.jsp">Data</a> | <a href="/cfp/privacy.jsp">Privacy Policy</a> | <a href="/cfp/terms.jsp">Terms and Conditions</a> </td></tr> <tr><td align="left"> Partners: <a 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PAKDD 2025 : 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining