Trends and Applications in Knowledge Discovery and Data Mining: PAKDD 2019 Workshops, BDM, DLKT, LDRC, PAISI, WeL, Macau, China, April 14–17, 2019, Revised Selected Papers

373 Pages·2019·32.398 MB·English

by  Leong Hou U., Hady W. Lauw

Leong Hou U.
Hady W. Lauw (Eds.)
Trends and Applications
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6 in Knowledge Discovery
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PAKDD 2019 Workshops
BDM, DLKT, LDRC, PAISI, WeL
Macau, China, April 14–17, 2019
Revised Selected Papers
123
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Lecture Notes in Arti cial Intelligence 11607
Subseries of Lecture Notes in Computer Science
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University of Alberta, Edmonton, Canada
Yuzuru Tanaka
Hokkaido University, Sapporo, Japan
Wolfgang Wahlster
DFKI and Saarland University, Saarbrücken, Germany
Founding Editor
Jörg Siekmann
DFKI and Saarland University, Saarbrücken, Germany
More information about this series at http://www.springer.com/series/1244
Leong Hou U. Hady W. Lauw (Eds.)
(cid:129)
Trends and Applications
in Knowledge Discovery
and Data Mining
PAKDD 2019 Workshops
BDM, DLKT, LDRC, PAISI, WeL
–
Macau, China, April 14 17, 2019
Revised Selected Papers
123
Editors
Leong HouU. Hady W.Lauw
University of Macau Singapore ManagementUniversity
Macao, China Singapore, Singapore
ISSN 0302-9743 ISSN 1611-3349 (electronic)
Lecture Notesin Artificial Intelligence
ISBN 978-3-030-26141-2 ISBN978-3-030-26142-9 (eBook)
https://doi.org/10.1007/978-3-030-26142-9
LNCSSublibrary:SL7–ArtificialIntelligence
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Preface
The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) is
oneofthelongestestablishedandleadinginternationalconferencesintheareasofdata
miningandknowledgediscovery.Itprovidesaninternationalforumforresearchersand
industry practitioners to share their new ideas, original research results, and practical
development experiences from all KDD-related areas, including data mining, data
warehousing, machine learning, artificial intelligence, databases, statistics, knowledge
engineering,visualization,decision-makingsystems,andtheemergingapplications.As
thefirstjointevent,PAKDD2019washeldinMacauSAR,China,duringApril14–17,
2019.
Along with the main conference, PAKDD workshops intend to provide an
international forum for researchers to discuss and share research results. After
reviewingtheworkshopproposals,wewereabletoacceptfiveworkshopsthatcovered
topics in intelligence and security informatics, weakly supervised learning, data
representation for clustering, biologically inspired techniques, and deep learning for
knowledgetransfer.Thediversityoftopicsintheseworkshopscontributedtothemain
themesoftheAPWeb-WAIMconference.Theseworkshopswereabletoaccept30full
papersthatwerecarefullyreviewedfrom52submissions.Thefiveworkshopswereas
follows:
– The 14th Pacific Asia Workshop on Intelligence and Security Informatics (PAISI
2019)
– PAKDD 2019 Workshop on Weakly Supervised Learning: Progress and Future
(WeL 2019),
– Learning Data Representation for Clustering (LDRC 2019),
– The 8th Workshop on Biologically Inspired Techniques for Knowledge Discovery
and Data Mining (BDM 2019)
– TheFirstPacificAsiaWorkshoponDeepLearningforKnowledgeTransfer(DLKT
2019)
July 2019 Hady W. Lauw
Leong Hou U.
Organization
Workshop Co-chairs
Hady W. Lauw Singapore Management University, Singapore
Leong Hou U. University of Macau, SAR China
The 14th Pacific Asia Workshop on Intelligence and Security
Informatics (PAISI 2019)
Workshop Co-chairs
Michael Chau The University of Hong Kong, SAR China
G. Alan Wang Virginia Tech, USA
Hsinchun Chen The University of Arizona, USA
Program Committee
Ahmed Abbasi Virginia Tech, USA
Indranil Bose Indian Institute of Management, Calcutta
Robert Chang Central Police University, Taiwan, China
Uwe Glasser Simon Fraser University, Canada
Eul Gyu Im Hanyang University, South Korea
Da-Yu Kao Central Police University, Taiwan, China
Siddharth Kaza Towson University, USA
Paul W. H. Kwan The University of New England, Australia
Mark Last Ben-Gurion University of the Negev, Israel
Ickjai Lee James Cook University, Australia
You-Lu Liao Central Police University, Taiwan, China
Hongyan Liu Tsinghua University, China
Hsin-min Lu National Taiwan University, Taiwan, China
Xin Robert Luo University of Minnesota, USA
Anirban Majumdar SAP Research, Germany
Byron Marshall Oregon State University, USA
Dorbin Ng The Chinese University of Hong Kong, SAR China
Shaojie Qiao Southwest Jiaotong University, China
Jialun Qin The University of Massachusetts Lowell, USA
Shrisha Rao IIIT-Bangalore, India
Srinath Srinivasa IIIT-Bangalore, India
Aixin Sun Nanyang Technological University, Singapore
Paul Thompson Dartmouth College, USA
Jau-Hwang Wang Central Police University, Taiwan, China
Shiuh-Jeng Wang Central Police University, Taiwan, China
Jennifer Xu Bentley University, USA
viii Organization
Yilu Zhou Fordham University, USA
William Zhu University of Electronic Science and Technology
of China, China
PAKDD 2019 Workshop on Weakly Supervised Learning:
Progress and Future (WeL 2019)
Organizing Committee
Yu-Feng Li Nanjing University, China
Sheng-Jun Huang Nanjing University of Aeronautics and Astronautics,
China
Learning Data Representation for Clustering (LDRC 2019)
General Chair
Mohamed Nadif Paris University Descartes, France
Program Co-chair
Lazhar Labiod Paris University Descartes, France
Workshop Organizers
Lazhar Labiod Paris University Descartes, France
Mohamed Nadif Paris University Descartes, France
Allou Same l’Institut français des sciences et technologies des
transports,del’aménagementetdesreseaux,France
Program Committee
Severine Affeldt Paris University Descartes, France
Salah Aghiles Singapore Management University, Singapore
Melissa Ailem USC Michelson Center, USA
Daniel Berrar Tokyo Institute of Technology, Japan
Patrice Bertrand CREMADE, Paris Dauphine University, France
Marc Boullé Orange Labs, France
Frabcusci de Assis Tenorio Universidade Federal de Pernambuco, Brazil
de Carvalho
Eruc Gaussier University Grenoble Alps, France
Salvatore Ingrassia University of Catania, Italy
Lazhar Labiod Paris University Descartes, France
Vincent Lemaire Orange Labs, France
Ahmed Moussa ENSAT, Abdelmalek Essaadi University, Morocco
Mohamed Nadif LIPADE, Paris University Descartes, France
François Role Paris University Descartes, France
Fabrice Rossi Université Paris 1 Panthéon-Sorbonne, France
Allou Same IFSTTAR, France
Organization ix
The 8th Workshop on Biologically-Inspired Techniques
for Knowledge Discovery and Data Mining (BDM 2019)
Program Chairs
Shafiq Alam University of Auckland, New Zealand
Gillian Dobbie University of Auckland, New Zealand
Program Committee
Patricia Riddle University of Auckland, New Zealand
Kamran Shafi University of New South Wales, Australia
Stephen Chen York University, Canada
Mengjie Zhang Victoria University, New Zealand
Kouroush Neshatian Victoria University, New Zealand
Ganesh Kumar Missouri University of Science
Venayagamoorthy and Technology, USA
Yanjun Yan Western Carolina University, USA
Mark Johnston Victoria University, New Zealand
Asifullah Khan Pakistan Institute of Engineering
and Applied Sciences, Pakistan
Bo Yuan Tsinghua University, China
Richi Nayak Queensland University of Technology, Australia
Faiz Rasol University of Auckland, New Zealand
The First Pacific Asia Workshop on Deep Learning
for Knowledge Transfer (DLKT 2019)
Organizers
Fuzhen Zhuang Institute of Computing Technology,
Chinese Academy of Sciences, China
Deqing Wang Beihang University, China
Pengpeng Zhao Soochow University, China
Contents
The 14th Pacific Asia Workshop on Intelligence and Security
Informatics (PAISI 2019)
A Supporting Tool for IT System Security Specification Evaluation
Based on ISO/IEC 15408 and ISO/IEC 18045 . . . . . . . . . . . . . . . . . . . . . . 3
Da Bao, Yuichi Goto, and Jingde Cheng
An Investigation on Multi View Based User Behavior Towards Spam
Detection in Social Networks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
Darshika Koggalahewa and Yue Xu
A Cluster Ensemble Strategy for Asian Handicap Betting. . . . . . . . . . . . . . . 28
Yue Chen and Jian Shi
Designing an Integrated Intelligence Center: New Taipei City Police
Department as an Example. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
Chun-Young Chang, Lin-Chien Chien, and Yuh-Shyan Hwang
Early Churn User Classification in Social Networking Service Using
Attention-Based Long Short-Term Memory . . . . . . . . . . . . . . . . . . . . . . . . 45
Koya Sato, Mizuki Oka, and Kazuhiko Kato
PAKDD 2019 Workshop on Weakly Supervised Learning:
Progress and Future (WeL 2019)
Weakly Supervised Learning by a Confusion Matrix of Contexts . . . . . . . . . 59
William Wu
Learning a Semantic Space for Modeling Images, Tags and Feelings
in Cross-Media Search. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
Sadaqat ur Rehman, Yongfeng Huang, Shanshan Tu,
and Basharat Ahmad
Adversarial Active Learning in the Presence of Weak
and Malicious Oracles. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
Yan Zhou, Murat Kantarcioglu, and Bowei Xi
The Most Related Knowledge First: A Progressive Domain
Adaptation Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
Yunyun Wang, Dan Zhao, Yun Li, Kejia Chen, and Hui Xue