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vertical-align:top; color:#666666;width:18.2981em; height:6.2379em;"> <iframe src="http://www.facebook.com/plugins/likebox.php?href=http%3A%2F%2Fwww.facebook.com%2Ffind-friends%2Findex.php%23%21%2Fpages%2FData-Mining-Machine-Learning-Community%2F144294218954736+&width=230&colorscheme=light&connections=0&stream=false&header=false&height=85" scrolling="no" frameborder="0" style="border:none; overflow:hidden; width:230px; height:85px;" allowTransparency="true"></iframe> </div> </div> </div> <div id="content"> <div class="block containingfloat"> <div class="left noborder"> <a name="top"></a> <h1>MLDM Call for Paper</h1> <p> <a href="#aim">The Aim of the Conference</a><br/> <a href="#topics">Topics of the conference</a><br/> <a href="#committee">Program Committee</a><br/> <a href="important_dates.php">Deadlines and Publications</a><br/> </p> <a name="aim"></a> <h2>The Aim of the Conference</h2> <p align="justify"> The aim of the conference is to bring together researchers from all over the world who deal with machine learning and data mining in order to discuss the recent status of the research and to direct further developments. Basic research papers as well as application papers are welcome. </p> <p align="justify">« <a href="#top">top</a></p> <a name="topics"></a> <h2>Topics of the conference</h2> <p align="justify"> All kinds of applications are welcome but special preference will be given to multimedia related applications, applications from live sciences and webmining. </p> <p align="justify"> Paper submissions should be related but not limited to any of the following topics: </p> <ul type="square"> <li><span class="text">association rules</span></li> <li><span class="text">case-based reasoning and learning</span></li> <li><span class="text">classification and interpretation of images, text, video</span></li> <li><span class="text">conceptional learning and clustering</span></li> <li><span class="text">Goodness measures and evaluaion (e.g. false discovery rates)</span></li> <li><span class="text">inductive learning including decision tree and rule induction learning</span></li> <li><span class="text">knowledge extraction from text, video, signals and images</span></li> <li><span class="text">mining gene data bases and biological data bases</span></li> <li><span class="text">mining images, temporal-spatial data, images from remote sensing</span></li> <li><span class="text">mining structural representations such as log files, text documents and HTML documents</span></li> <li><span class="text">mining text documents</span></li> <li><span class="text">organisational learning and evolutional learning</span></li> <li><span class="text">probabilistic information retrieval</span></li> <li><span class="text">Sampling methods</span></li> <li><span class="text">Selection with small samples</span></li> <li><span class="text">similarity measures and learning of similarity</span></li> <li><span class="text">statistical learning and neural net based learning</span></li> <li><span class="text">video mining</span></li> <li><span class="text">visualization and data mining</span></li> <li><span class="text">Applications of Clustering</span></li> <li><span class="text">Aspects of Data Mining</span></li> <li><span class="text">Applications in Medicine</span></li> <li><span class="text">Autoamtic Semantic Annotation of Media Content</span></li> <li><span class="text">Bayesian Models and Methods</span></li> <li><span class="text">Case-Based Reasoning and Associative Memory</span></li> <li><span class="text">Classification and Model Estimation </span></li> <li><span class="text">Content-Based Image Retrieval</span></li> <li><span class="text">Decision Trees</span></li> <li><span class="text">Deviation and Novelty Detection</span></li> <li><span class="text">Feature Grouping, Discretization, Selection and Transformation</span></li> <li><span class="text">Feature Learning</span></li> <li><span class="text">Frequent Pattern Mining</span></li> <li><span class="text">High-Content Analysis of Microscopic Images in Medicine, Biotechnology and Chemistry</span></li> <li><span class="text">Learning and adaptive control</span></li> <li><span class="text">Learning/adaption of recognition and perception</span></li> <li><span class="text">Learning for Handwriting Recognition</span></li> <li><span class="text">Learning in Image Pre-Processing and Segmentation</span></li> <li><span class="text">Learning in process automation</span></li> <li><span class="text">Learning of internal representations and models</span></li> <li><span class="text">Learning of appropriate behaviour</span></li> <li><span class="text">Learning of action patterns</span></li> <li><span class="text">Learning of Ontologies</span></li> <li><span class="text">Learning of Semantic Inferencing Rules</span></li> <li><span class="text">Learning of Visual Ontologies</span></li> <li><span class="text">Learning robots</span></li> <li><span class="text">Mining Images in Computer Vision</span></li> <li><span class="text">Mining Images and Texture</span></li> <li><span class="text">Mining Motion from Sequence</span></li> <li><span class="text">Neural Methods</span></li> <li><span class="text">Network Analysis and Intrusion Detection</span></li> <li><span class="text">Nonlinear Function Learning and Neural Net Based Learning</span></li> <li><span class="text">Real-Time Event Learning and Detection</span></li> <li><span class="text">Retrieval Methods</span></li> <li><span class="text">Rule Induction and Grammars</span></li> <li><span class="text">Speech Analysis</span></li> <li><span class="text">Statistical and Conceptual Clustering Methods</span></li> <li><span class="text">Statistical and Evolutionary Learning</span></li> <li><span class="text">Subspace Methods</span></li> <li><span class="text">Support Vector Machines</span></li> <li><span class="text">Symbolic Learning and Neural Networks in Document Processing</span></li> <li><span class="text">Time Series and Sequential Pattern Mining</span></li> <li><span class="text">Audio Mining</span></li> <li><span class="text">Cognition and Computer Vision</span></li> <li>Clustering</li> <li>Classification & Prediction</li> <li>Statistical Learning</li> <li>Association Rules</li> <li>Telecommunication</li> <li>Design of Experiment</li> <li>Strategy of Experimentation</li> <li>Capability Indices</li> <li>Deviation and Novelty Detection</li> <li>Control Charts</li> <li>Design of Experiments</li> <li>Capability Indices</li> <li>Conceptional Learning</li> <li>Goodness Measures and Evaluation (e.g. false discovery rates)</li> <li>Inductive Learning Including Decision Tree and Rule Induction Learning</li> <li>Organisational Learning and Evolutional Learning</li> <li>Sampling Methods</li> <li>Similarity Measures and Learning of Similarity</li> <li>Statistical Learning and Neural Net Based Learning</li> <li>Visualization and Data Mining</li> <li>Deviation and Novelty Detection</li> <li>Feature Grouping, Discretization, Selection and Transformation</li> <li>Feature Learning</li> <li>Frequent Pattern Mining</li> <li>Learning and Adaptive Control</li> <li>Learning/Adaption of Recognition and Perception</li> <li>Learning for Handwriting Recognition</li> <li>Learning in Image Pre-Processing and Segmentation</li> <li>Mining Financial or Stockmarket Data</li> <li>Mining Motion from Sequence</li> <li>Subspace Methods</li> <li>Support Vector Machines</li> <li>Time Series and Sequential Pattern Mining</li> <li>Desirabilities</li> <li>Graph Mining</li> <li>Agent Data Mining</li> <li>Applications in Software Testing</li> </ul> <p> </p> <p>Authors can submit their paper in long or short version.</p> <h3>Long Paper</h3> <p align="justify"> The paper must be formatted in the Springer LNCS format. They should have at most 15 pages. The papers will be reviewed by the program committee. </p> <h3>Short Paper</h3> <p align="justify"> Short papers are also welcome and can be used to describe work in progress or project ideas. They can have 5 to max. 15 pages, formatted in Springer LNCS format. Accepted short papers will be presented as poster in the poster session. They will be published in a special poster proceedings book.</p>  <p>« <a href="#top">top</a></p> <a name="committee"></a> <h2>Program Committee</h2> <table> <tbody> <tr> <th>Chair</th> <th></th> </tr> <tr> <td class="last td_widther"><a href="http://www.ibai-research.de" onclick="window.open(this.href,'_blank');return false">Petra Perner</a></td> <td class="last td_left">IBaI, Germany</td> </tr> <tr> <th>Committee</th> <th></th> </tr> <tr> <td class="td_widther">Piotr Artiemjew</a></td> <td class="td_left">University of Warmia and Mazury in Olsztyn, Poland</td> </tr> <tr> <td class="td_widther">Ming-Ching Chang</td> <td class="td_left">University of Albany, USA</td> </tr> <tr> <td class="td_widther">Robert Haralick</td> <td class="td_left">City University of New York, USA</td> </tr> <tr> <td class="td_widther">Chih-Chung Hsu</td> <td class="td_left">National Cheng Kung University, Taiwan</td> </tr> <tr> <td class="td_widther">Adam Krzyzak</td> <td class="td_left">Concordia University, Canada</td> </tr> <tr> <td class="td_widther">Krzysztof Pancerz</td> <td class="td_left">Academy of Zamosc, Poland</td> </tr> <tr> <td class="td_widther">M. Zakeria Kurdi</td> <td class="td_left">University of Lynchburg, USA</td> </tr> <tr> <td class="td_widther">Dan Simovici</td> <td class="td_left">University of Massachusetts Boston, USA</td> </tr> <tr> <td class="td_widther">Tanveer Syeda-Mahmood</td> <td class="td_left">IBM Almaden Research Center, USA</td> </tr> <tr> <td class="td_widther">Yi Wei</td> <td class="td_left">Samsung Research America Inc., USA</td> </tr> <tr> <td class="td_widther">Agnieszka Wosiak</td> <td class="td_left">Lodz University of Technology, Poland</td> </tr> </tbody> </table> <p align="justify"> An industrial exhibition running in connection with the conference will give you the opportunity to look at new trends and systems in industry and to present your research to industry. </p> <p>« <a href="#top">top</a></p> <h2>Deadlines</h2> <p><a href="important_dates.php">more Information</a></p> </div> <div class="right"> <div class="box"> <img src="img/154_registration.gif" alt="Registration" title="Registration"/> <p> <a href="registration.php">Register here</a> <a href="https://easychair.org/conferences/?conf=mldm2022" onclick="window.open(this.href,'_blank');return false">Submit your paper</a> </p> </div> <img class="pic" src="img/156_vortrag.jpg" alt="presentation © Shutterstock" title="presentation"/> <img class="pic" src="img/156_vortrag1.jpg" alt="presentation © Petra Perner" title="presentation"/> <img class="pic" src="img/156_referat.jpg" alt="presentation © Shutterstock" title="presentation"/> </div> </div> </div> </body> </html>