The WSDM 2019 Workshop on Interactive Data Mining

The WSDM 2019 Workshop on Interactive Data Mining

We are pleased to announce the Workshop on Interactive Data Mining co-located with WSDM 2019 in Melbourne, Australia.

Now the WIDM'19 proceedings are located at ACM Digital Library.
You can view the proceedings material using the following URL: http://dl.acm.org/citation.cfm?id=3304079.

Program

Time Title
1:30 - 2:15 Keynote Interactive Visual Data Mining of Big Complex Networks
Seokhee Hong, University of Sydney
2:15 - 2:35 Paper Smart Farm: A System for Proactive Management of Raw Milk Quality
Atefe Zakeri, Morteza Saberi, Saeed Aboutalebi, Omar Hussain and Elizabeth Chang
2:35 - 2:55 Paper Interactive Clustering for Exploring Multiple Data Streams at Different Time Scales and Granularity
Anders Holst, Juhee Bae, Alexander Karlsson and Mohamed-Rafik Bouguelia
3:00 - 3:30 Coffee Break
3:30 - 3:50 Paper Incremental Causal Discovery and Visualization
Anders Holst, Sepideh Pashami and Juhee Bae
3:50 - 4:10 Paper Interactive feature extraction for diagnostic trouble codes in predictive maintenance A case study from automotive domain
Parivash Pirasteh, Sławomir Nowaczyk and Sepideh Pashami
4:10 - 4:30 Paper Interactive-COSMO: Consensus Self-Organized Models for Fault Detection with Expert Feedback
Ece Calikus, Yuantao Fan, Slawomir Nowaczyk and Anita Sant'Anna
4:30 - 5:00 Discussion

Objectives

In the age of Big Data, Artificial Intelligence, and Data Mining, an aspect often overlooked is the interactive and visual usability of frameworks, tools, and concepts used for ingesting and analyzing large quantities of data. This workshop focuses on aspects related to exactly this, i.e. how do we improve the interaction and usability of modern data mining approaches and how do make them accessible, understandable, and useful to non-experts.
Taking an agnostic view of the application scenario, the workshop intends to serve as a forum for researchers and practitioners working at all levels of abstraction with data mining technologies. Interaction and interactive in the context of the workshop should be seen as anything from UI/UX-related aspects of visual interfaces, to more hands-on interaction with software and hardware used in the general areas of data mining, machine learning, and other concepts related broadly to artificial intelligence.
The aim of this workshop is to explore existing and new interactive methods in machine learning and data mining that help the users to take better, and more informed, decisions. The primary audience of the workshop are researchers and practitioners in data mining from academia and industry with an interest in interaction with and interactivity of data mining approaches.

We invite submissions that may include the following topics, but are not limited to:

The goal of this workshop is to share and discuss research and projects that focus on interaction with and interactivity of data mining systems.

Invited Speaker

Seokhee Hong is a professor at the University of Sydney. She was an ARC Future Fellow, a Humboldt Fellow, ARC Research Fellow, and a project leader of VALACON (Visualisation and Analysis of Large and Complex Networks) project at NICTA. Her research interests include Graph Drawing, Algorithms, Information Visualisation and Visual Analytics. She serves as a Steering Committee member of IEEE PacificVis (International Symposium on Pacific Visualisation) and ISAAC (International Symposium on Algorithms and Computations), and an editor of JGAA (Journal of Graph Algorithms and Applications).

Interactive Visual Data Mining of Big Complex Networks

Recent technological advances have led to big complex data models in many domains, including social networks and biological networks. Visual Data Mining can reveal the hidden structure of the networks and amplifies human understanding, thus leading to new insights and findings. However, interactive visualisation of big complex networks is challenging due to scalability and complexity. This talk will introduce a framework for Visual Analytics of big complex networks, and review latest methods for visual analytics of such networks including new quality metrics.

Submission

Papers must be submitted in PDF according to the new ACM Guidelines.

Single-blind peer review format will be used. We welcome submissions in either long or short format. 4-pages submissions are considered as short paper and 6-8 pages submissions are considered as long papers, plus up to one additional page of references. Submitted papers will be reviewed by at least two independent referees from the Program Committee.

Papers must be submitted electronically via EasyChair at https://easychair.org/conferences/?conf=wsdmidm2019.

Accepted long papers will be published through SIG Services.

Important dates

Committee

Workshop Chairs

Program Committee

Venue

Location

Please visit the WSDM 2019 website for more information about the location: http://www.wsdm-conference.org/2019/venue.php

Contact

If you have questions regarding the workshop, do not hesitate to contact the workshop chairs.

© Workshop on Interactive Data Mining