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                                  Preface


    Recent advances in Deep Learning have helped to usher in a new wave of
confidence in the capability of artificial intelligence. Increasingly, we are see-
ing DL architectures outperform long established state-of-the-art algorithms in
a number of diverse tasks. In fact, DL has reached a point where it currently
rivals or has surpassed human performance in a number of challenges e.g. im-
age classification, speech recognition and board games. The successes of Deep
Learning call for novel methods and techniques that exploit Deep Learning for
the benefit of Case-based reasoning (CBR). The potentials of Deep Learning
for CBR include improvement in knowledge aggregation and feature extraction
for case representation, efficient indexing and retrieval architectures as well as
assisting with case adaptation.
    In this first edition of the ICCBR Workshop on Case-Based Reasoning and
Deep Learning, 3 papers have been accepted for presentation from researchers
from UK and Norway. The first contribution uses Siamese Neural Networks
to facilitate learning similarity knowledge for reasoning with time series data.
The second contribution describes using Deep Convolutional Neural Networks
(CNNs) to learn feature representations from accelerometer data for kNN-based
human activity recognition. The third contribution presents the use of Deep
Learning to predict favourable operating windows for ships, given weather con-
ditions. This information is then used within a CBR system for planning op-
erations in aquaculture installations. The submissions collectively demonstrate
useful opportunities where Deep Learning has been leveraged within CBR sys-
tems with promising results.


June 2017                                     Sadiq Sani and Stewart Massie
                                                            Program Chairs
                     Case-Based Reasoning and Deep Learning Workshop, 2017
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                           Organization


Organizing Committee
Sadiq Sani (Robert Gordon University, UK)
Stewart Massie (Robert Gordon Univerity, UK)


Program Committee
Kerstin Bach (Norwegian University of Science and Technology, Norway)
Marc Pickett (Google, USA)
Michael Floyd (Knexus Research Corporation , USA)
Nirmalie Wiratunga (Robert Gordon University, UK)
Kajzon Grace (University of North Carolina at Charlotte, USA)