Room1 Room2 Room3
8:50 - 9:00 ISMIS 2018 Opening & DS Opening
9:00 - 10:00 ISMIS INVITED TALK Bridging the Gap between Data Diversity and Data Dependencies, Jean-Marc Petit, chair: Jiming Liu
10:00 - 10:30 Best student Paper ISMIS: Exploiting Order Information Embedded in Ordered Categories for Ordinal Data Clustering (Yiqun Zhang and Yiu-Ming Cheung)
10:30 - 11:00 Coffee Break
11:00 - 12:40 Session 1A: Graph Mining Session1B: Intelligent Methodologies for Traffic Data Analysis and Mining (SS) Session 1: Classification
12:40 - 14:00 Lunch
14:00 - 15:00 ISMIS INVITED TALK Mining Big and Complex Data, Sašo Džeroski, chair: Nathalie Japkowicz
15:00 - 16:00 Session 2A: Advanced Methods in Machine Learning for Modeling Complex Data (SS) Session 2B: Intelligent Methodologies for Traffic Data Analysis and Mining (SS) Session 2: Mixed session: Rule learning; Reinforcement Learning; Text mining
16:00 - 16:30 Coffee Break
16:30 - 18:30 Session 3A: Advanced Methods in Machine Learning for Modeling Complex Data (SS) Session 3B: Graph Mining and Social Data Session 3: Text mining
19:00- 20:00 Welcome reception
 
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ISMIS2018

Session 1A : Graph Mining

  • Solving the Maximal Clique Problem on Compressed Graphs Jocelyn Bernard and Hamida Seba
  • Clones in Graphs Stephan Doerfel, Tom Hanika and Gerd Stumme
  • Knowledge-Based Mining of Exceptional Patterns in Logistics Data: Approaches and Experiences in an Industry 4.0 Context Eric Sternberg and Martin Atzmueller
 

Session 1B : Intelligent Methodologies for Traffic Data Analysis and Mining (SS)

  • An Approach for the Police Districting Problem using Artificial Intelligence Jose Manuel Rodriguez Jimenez
  • Unsupervised LSTMs-based Learning for Anomaly Detection in Highway Traffic Data Nicola Di Mauro and Stefano Ferilli
  • A Big Data framework for analysis of traffic data in Italian highways Claudia Diamantini, Domenico Potena and Emanuele Storti
 

Session 2A : Advanced Methods in Machine Learning for Modeling Complex Data (SS)

  • Sparse Multi-Label Bilinear Embedding on Stiefel Manifolds Yang Liu, Guohua Dong and Zhonglei Gu
  • Learning Latent Factors in Linked Multi-Modality Data Tiantian He and Keith C.C. Chan

Session 2B : Intelligent Methodologies for Traffic Data Analysis and Mining (SS)

  • Unsupervised vehicle recognition using incremental reseeding of acoustic signatures Justin Sunu, Allon G. Percus and Blake Hunter
  • Traffic Data Classification for Police Activity Stefano Guarino, Fabio Leuzzi, Flavio Lombardi and Enrico Mastrostefano
 

Session 3A : Advanced Methods in Machine Learning for Modeling Complex Data (SS)

  • Researcher Name Disambiguation:Feature Learning and Affinity Propagation Clustering Zhizhi Yu and Bo Yang
  • Hierarchical Clustering of High-Dimensional Data without Global Dimensionality Reduction Ilari Kampman and Tapio Elomaa
  • User-emotion detection through sentence-based classification using Deep Learning: a case-study with Microblogs in Albanian. Marjana Prifti Skenduli, Marenglen Biba, Corrado Loglisci and Donato Malerba
  • A Novel Personalized Citation Recommendation Approach based on GAN Ye Zhang, Libin Yang, Xiaoyan Cai and Hang Dai

Session 3B : Graph Mining and Social Data

  • An Intra-algorithm Comparison Study of Complete Search FSM Implementations in Centralized Graph Transaction Databases Rihab Ayed, Mohand-Said Hacid, Rafiqul Haque and Abderrazak Jemai
  • Critical Link Identification based on Bridge Detection for Network with Uncertain Connectivity Kazumi Saito, Kouzou Ohara, Masahiro Kimura and Hiroshi Motoda
  • Market-aware Proactive Skill Posting Ashiqur Khudabukhsh, Jong Woo Hong and Jaime Carbonell
  • Evidential Multi-relational Link Prediction Based on Social Content Sabrine Mallek, Imen Boukhris, Zied Elouedi and Eric Lefevre
 

DS2018

Session 1 : Classification

  • Addressing Local Class Imbalance in Balanced Datasets with Dynamic Impurity Decision Trees Andriy Mulyar and Bartosz Krawczyk
  • Barricaded Boundary Minority Oversampling LS-SVM for a Biased Binary Classification Hmayag Partamian, Yara Rizk and Mariette Awad
  • Dynamic Classifier Chain with Random Decision Trees Moritz Kulessa and Eneldo Loza Mencia
  • Feature Ranking with Relief for Multi-label classification: Does distance matter? Matej Petković, Dragi Kocev and Sašo Džeroski
  • Leveraging Reproduction-Error Representations for Multi-Instance Classification Sebastian Kauschke, Max Mühlhäuser and Johannes Fürnkranz
 

Session 2 : Mixed session: Rule learning; Reinforcement Learning; Text mining

  • Finding Probabilistic Rule Lists using the Minimum Description Length Principle John Aoga, Tias Guns, Siegfried Nijssen and Pierre Schaus
  • Preference-based Reinforcement Learning using Dyad Ranking Dirk Schäfer and Eyke Huellermeier
  • Filtering Documents for Plagiarism Detection Kensuke Baba
 

Session 3 : Text mining

  • k-NN Embedding Stability for word2vec Hyper-parametrisation in Scientific Text Amna Dridi, Mohamed Medhat Gaber, R. Muhammad Atif Azad and Jagdev Bhogal
  • WS4ABSA: an NMF-based Weakly-Supervised Approach for Aspect-Based Sentiment Analysis with Application to Online Reviews Alberto Purpura, Chiara Masiero and Gian Antonio Susto
  • Author Tree-structured Hierarchical Dirichlet Process Md. Hijbul Alam, Jaakko Peltonen, Jyrki Nummenmaa and Kal Järvelin
  • Most Important First - Keyphrase Scoring for Improved Ranking in Settings With Limited Keyphrases Nils Witt, Tobias Milz and Christin Seifert
  • Hierarchical Expert Profiling using Heterogeneous Information Networks Jorge Silva, Pedro Ribeiro and Fernando Silva
Room1 Room2 Room3
9:00 - 10:00 INVITED: ISMIS/DS Artificial Intelligence and the Industrial Knowledge Graph, Michael May, chair: Michelangelo Ceci
10:00 - 10:30 Best Paper ISMIS: An Efficient Algorithm for Network Vulnerability Analysis under Malicious Attacks (Toni Mancini, Federico Mari, Igor Melatti, Ivano Salvo and Enrico Tronci)
10:30 - 11:00 Coffee Break
11:00 - 12:30 Session 4A: Bioinformatics and Health Informatics Session 4B: Granular and Soft Clustering for Data Science (SS) Session 4: AutoML and Meta-learning
12:30 - 14:00 Lunch
14:00 - 15:00 DS tutorial: Emojis, Sentiment and Stance in Social Media, Petra Kralj Novak, chair: Larisa Soldatova
15:00 - 16:00 Session 5A:Image Analysis Session 5B: Granular and Soft Clustering for Data Science (SS) Session 5: Subgroup and subgraph discovery
16:00 - 16:30 Coffee Break
16:30 - 18:30 Session 6A: Spatio-Temporal Data Analysis Session 6B: Topic Modelling and Opinion Mining Session 6: Applications
18:00-19:00 DS community meeting
DS SC Meeting
19:30 GALA DINNER
 
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ISMIS2018

Session 4A : Bioinformatics and Health Informatics

  • Fully automatic classification of flow cytometry data Bartosz P. Piotrowski and Miron B. Kursa
  • Positive Unlabeled Link Prediction via Transfer Learning for Gene Network Reconstruction Paolo Mignone and Gianvito Pio
  • Rough Sets: Visually Discerning Neurological Functionality During Thought Processes Rory Lewis, Chad A. Mello, Yanyan Zhuang, Martin K. -C. Yeh, Dan Gopstein and Yu Yan
 

Session 4B : Granular and Soft Clustering for Data Science (SS)

  • An Adaptive Three-way Clustering Algorithm for Mixed-type Data Jing Xiong and Hong Yu
  • Three-way Spectral Clustering Hong Shi, Qiang Liu and Pingxin Wang
  • The Granular Structures in Formal Concept Analysis Ruisi Ren and Ling Wei
 

Session 5A : Image Analysis

  • Deep Neural Networks for Face Recognition: Pairwise Optimisation Elitsa Popova, Athanasios Athanasopoulos, Efraim Ie, Nikolaos Christou and Ndifreke Nyah
  • A Comparative Study on Soft Biometric Approaches to be Used in Retail Stores Berardina Nadja De Carolis, Nicola Macchiarulo and Giuseppe Palestra

Session 5B : Granular and Soft Clustering for Data Science (SS)

  • From Knowledge Discovery to Customer Attrition Katarzyna Tarnowska and Zbigniew Ras
  • Initial Analysis of Multivariate Factors for Prediction of Shark Presence and Attacks on the Coast of North Carolina Sonal Kaulkar, Lavanya Vinodh and Pamela Thompson
 

Session 6A: Spatio-Temporal Data Analysis

  • Predicting Temporal Activation Patterns via Recurrent Neural Networks Giuseppe Manco, Giuseppe Pirrò and Ettore Ritacco
  • Handling Multi-Scale Data via Multi-Target Learning for Wind Speed Forecasting Annalisa Appice, Antonietta Lanza and Donato Malerba
  • Luca Anselma, Alessandro Mazzei, Luca Piovesan and Paolo Terenziani Temporal Reasoning with Layered Preferences

Session 6B: Topic Modelling and Opinion Mining

  • An Experimental Evaluation of Algorithms for Opinion Mining in Multi-Domain Corpus in Albanian Nelda Kote, Marenglen Biba and Evis Trandafili
  • Predicting Author’s Native Language Using Abstracts of Scholarly Papers Takahiro Baba, Kensuke Baba and Daisuke Ikeda
  • Identifying Exceptional Descriptions of People using Topic Modeling and Subgroup Discovery Andrew Hendrickson, Jason Wang and Martin Atzmueller
 

DS2018

Session 4: AutoML and Meta-learning

  • MetaUtil: Meta Learning for Utility Maximization in Regression Paula Branco, Luis Torgo and Rita P. Ribeiro
  • Predicting Rice Phenotypes with Meta-Learning Oghenejokpeme Orhobor, Nickolai Alexandrov and Ross King
  • CF4CF-META: Hybrid Collaborative Filtering Algorithm Selection Framework Tiago Cunha, Carlos Soares and Andre de Carvalho
  • Class Balanced Similarity-Based Instance Transfer Learning for Botnet Family Classification Basil Alothman, Helge Janicke and Suleiman Yerima
 

Session 5: Subgroup and subgraph discovery

  • Extending redescription mining to multiple views Matej Mihelčić, Saso Dzeroski and Tomislav Smuc
  • Compositional Subgroup Discovery on Attributed Social Interaction Networks Martin Atzmueller
  • Exceptional attributed subgraph mining to understand the olfactory percept Maëlle Moranges, Marc Plantevit, Arnaud Fournel, Moustafa Bensafi and Celine Robardet
 

Session 6: Applications

  • Identifying control parameters in cheese fabrication process using precedence constraints Melanie Munch, Pierre-Henri Wuillemin, Juliette Dibie-Barthélemy, Cristina Manfredotti, Thomas Allard, Solange Buchin and Elisabeth Guichard
  • Less is More: Univariate Modelling to Detect Early Parkinson's Disease from Keystroke Dynamics Antony Milne, Katayoun Farrahi and Mihalis Nicolaou
  • Sky Writer: Towards an Intelligent Smart-phone Gesture Tracing and Recognition Framework Nicolas Mitri and Mariette Awad
  • Visualization and analysis of Parkinson's disease status and therapy patterns Anita Valmarska, Dragana Miljkovic, Marko Marko Robnik-Šikonja and Nada Lavrač
  • Finding Topic-specific Trends and Influential Users in Social Networks Eleni Koutrouli, Christos Daskalakis and Aphrodite Tsalgatidou
 
Room1 Room2 Room3
9:00 - 10:00 INVITED: DS Automating Predictive Modeling and Knowledge Discovery, Ioannis Tsamardinos, chair: Joaquin Vanschoren
10:00 - 10:30 Best Paper DS (Carl H. Smith Award Talk)
10:30 - 11:00 Coffee Break
11:00 - 12:40 Session 7A: Intelligent Systems Session 7B: Applications Session 7: Streams and Time series
12:40 - 13:00 Closing
13:00 - 14:00 Lunch
 
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ISMIS2018

Session 7A : Intelligent Systems

  • SCUT-DS: Learning from Multi-class Imbalanced Canadian Weather Data Olubukola Olaitan and Herna Viktor
  • An Instrumented Methodology to Analyze and Categorize Information Flows on Twitter Using NLP and Deep Learning : A Use Case on Air Qualit Brigitte Juanals and Jean-Luc Minel
  • Multipurpose Web-Platform for Labeling Audio Segments Efficiently and Effectively Ayman Hajja, Griffin Hiers, Pierre Arbajian, Zbigniew Ras and Alicja Wieczorkowska
  • A Description Logic of Typicality for Conceptual Combination Antonio Lieto and Gian Luca Pozzato
 

Session 7B : Applications

  • Mobile Application with Image Recognition for Persons with Aphasia Jan Gonera, Krzysztof Szklanny, Marcin Wichrowski and Alicja Wieczorkowska
  • Early Detection of Heart Symptoms with Convolutional Neural Network and Scattering Wavelet Transformation Mariusz Kleć
  • Low Resources Intelligent System for the 2D Biomechanical Analysis of Road Cyclists Camilo Salguero Marín, Sandra Mosquera, Andrés Felipe Barco Santa and Elise Vareilles
  • Fuzzy RST and RST rules can predict effects of different therapies in Parkinson’s disease patients Andrzej W. Przybyszewski
 

DS2018

Session 7 : Streams and Time series

  • Self Hyper-parameter Tuning for Data Streams Bruno Veloso, João Gama and Benedita Malheiro
  • Selection of Relevant and Non-Redundant Multivariate Ordinal Patterns for Time Series Classification Arvind Kumar Shekar, Marcus Pappik, Emmanuel Mueller and Patricia Iglesias Sanchez
  • COBRAS-TS: A new approach to Semi-Supervised Clustering of Time Series Toon Van Craenendonck, Wannes Meert, Sebastijan Dumancic and Hendrik Blockeel
  • Exploiting the Web for Semantic Change Detection Pierpaolo Basile and Barbara McGillivray
  • Online boosting for incremental recommender systems João Vinagre, Alipio M. Jorge and Joao Gama