DM algorithms tat produce Symbolic models, or approaches that extract useful knowledge from black-box models are very useful tools to propose explanations that could help experts to understand better the domain. This workshop addresses such concerns. The workshop will be concerned with the exchange of experience among researchers and provide updated knowledge concerning the extraction of useful domain knowledge either by directly using symbolic DM algorithms or post-processing non-symbolic ones.
Workshop on Intelligible Data Mining models for Bioinformatics and Chemoinformatics
(IntDMBC 2019)
(https://intdmbc2019.fe.up.pt)
as part of IEEE ICDM 2019
(http://icdm2019.bigke.org/)
To be held in Beijing, China, 8th November 2019 Aims and Scope
Science is about understanding! Although Data Mining (DM) has been extremely useful in a large number of domains where data analysis is necessary, most of the concerns of the DM users has been the development of highly accurate models according to some pre-specified metrics. Those concerns are completely justified and enough for a wide range application like predicting stock exchange market, for example. However, in Scientific applications like the Live Sciences or Chemistry a good performance according to the evaluation metric is most often not enough and an explanation for the phenomena that produced the data is requited. DM algorithms tat produce Symbolic models, or approaches that extract useful knowledge from black-box models are very useful tools to propose explanations that could help experts to understand better the domain. This workshop addresses such concerns. The workshop will be concerned with the exchange of experience among researchers and provide updated knowledge concerning the extraction of useful domain knowledge either by directly using symbolic DM algorithms or post-processing non-symbolic ones.
Topics of interest
The topics of interest include (but not restricted to) the following ones:
* Novel symbolic Machine Learning algorithms
* Novel post-processing approaches to extract knowledgeable information from black-box systems
* Applications of symbolic data mining systems in Bioinformatics
* Applications of symbolic data mining systems in Chemoinformatics
* Data Mining support tools to obtain intelligible knowledge from data
Important Dates:
Paper submission deadline August 7th, 2019
Paper acceptance notification September 4th, 2019
Paper camera-ready deadline September 8th, 2019:
IntDMBC 2019 Workshop November 8th, 2019
Paper Submission Guidelines
Submissions must be original (not previously published and not under review in other forums). Authors should follow IEEE ICDM Proceedings Author Guidelines. The regular research papers length must have a maximum of 10 pages (references, figures, tables and appendices already included). REMARK that the camera-ready copy must be 8 pages (2 extra - chargeable - pages are, however allowed). Papers should be submitted using Cyberchair (https://wi-lab.com/cyberchair/2019/icdm19/scripts/ws_submit.php?subarea=S). Submitted papers will be evaluated by three PC members. Blind reviewing will be used. All accepted papers will be included in the IEEE ICDM 2019 Workshops Proceedings volume published by IEEE Computer Society Press, and will also be included in the IEEE Xplore Digital Library.
Program Chairs:
Rui Camacho (LIAAD, INESC TEC & DEI & FEUP Universidade do Porto, Portugal)
Vítor Santos Costa (CRACS, INESCTEC & FCUP, University of Porto, Portugal)
Inês Dutra (CINTESIS, INESCTEC & FCUP, University of Porto, Portugal)
Nuno Fonseca Nuno Fonseca (CiBIO Universidade do Porto, Portugal)
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