Discovery Science 2014

Acepted Presentations

Prem Raj Adhikari, Anže Vavpetič, Jan Kralj, Nada Lavrač and Jaakko Hollmén.
Explaining mixture models through semantic pattern mining and banded matrix visualization
Nino Antulov-Fantulin, Matko Bosnjak, Vinko Zlatić, Miha Grčar and Tomislav Šmuc.
Synthetic sequence generator for recommender systems - memory biased random walk on sequence multilayer network
Xi Hang Cao, Ivan Stojković and Zoran Obradović.
Predicting Sepsis Severity from Limited Temporal Observations
Michelangelo Ceci, Pasqua Fabiana Lanotte, Fabio Fumarola, Dario Pietro Cavallo and Donato Malerba.
Completion Time and Next Activity Prediction of Processes using Sequential Pattern Mining
Darrell Conklin and Stephanie Weisser.
Antipattern discovery in Ethiopian bagana songs
Tal Galili, Alexis Mitelpunkt, Netta Shachar, Mira Marcus-Kalish and Yoav Benjamini.
Categorize, Cluster and Classify: a 3-C strategy for scientific discovery in the Medical Informatics platform of the Human Brain Project
Dragan Gamberger, Matej Mihelčić and Nada Lavrač.
Multilayer clustering: A discovery experiment on country level trading data
Nicolau Gonçalves, Erkki Oja and Ricardo Vigário.
Document mining combining image exploration and text characterization
Tayena Hendrickx, Boris Cule and Bart Goethals.
Mining Cohesive Itemsets in Graphs
Sascha Henzgen and Eyke Huellermeier.
Mining rank data
Andrej Kastrin, Thomas C. Rindflesch and Dimitar Hristovski.
Link Prediction on Semantic MEDLINE Network: An Approach to Literature-based Discovery
Ivan Kitanovski, Ivica Dimitrovski, Gjorgji Madzarov and Suzana Loskovska.
Medical Image Retrieval using Multimodal Data
Seiichi Kondo, Keisuke Otaki, Madori Ikeda and Akihiro Yamamoto.
Fast Computation of The Tree Edit Distance Between Unordered Trees Using IP Solvers
Georg Krempl, Daniel Kottke and Myra Spiliopoulou.
Probabilistic Active Learning: Towards Combining Versatility, Optimality and Efficiency
Pawel Matuszyk and Myra Spiliopoulou.
Selective Forgetting for Incremental Matrix Factorization in Recommender Systems
Eneldo Loza Mencia and Frederik Janssen.
Stacking Label Features for Learning Multilabel Rules
Sandy Moens, Mario Boley and Bart Goethals.
Providing Concise Database Covers Instantly by Recursive Tile Sampling
Alya Al Nasseri and Allan Tuckar.
Bayesian Network Model for predicting Stock Micro-Blogging Sentiments in Stock Market
Kouzou Ohara, Kazumi Saito, Masahiro Kimura and Hiroshi Motoda.
Resampling-based Framework for Estimating Node Centrality of Large Social Network
Yoshiaki Okubo, Masanobu Matsudaira and Makoto Haraguchi.
Detecting Maximum k-Plex with Iterative Proper l-Plex Search
Bidyut Kr. Patra, Raimo Launonen, Ville Ollikainen and Sukumar Nandi.
Exploiting Bhattacharyya similarity measure to diminish user cold-start problem in sparse data
Pedro Pereira, Rita Ribeiro and João Gama.
Failure Prediction - an Application in the Railway Industry
Sonja Pravilović, Annalisa Appice, Antonietta Lanza and Donato Malerba.
Wind Power Forecasting using Time Series Cluster Analysis
Jan van Rijn, Bernhard Pfahringer, Geoffrey Holmes and Joaquin Vanschoren.
Algorithm Selection Problem in Stream Mining
Petar Ristoski and Heiko Paulheim.
Feature Selection in Hierarchical Feature Spaces
Duc Kinh Le Tran, Cecile Bothorel, Pascal Cheung Mon Chan and Yvon Kermarrec.
Incremental learning with social media data to predict near real-time events
Neda Trifonova, Daniel Duplisea, Andrew Kenny, David Maxwell and Allan Tucker.
Incorporating Regime Metrics into Latent Variable Dynamic Models to Detect Early-Warning Signals of Functional Changes in Fisheries Ecology
Takeaki Uno and Hiroko Satoh.
An Efficient Algorithm for Enumerating Chordless Cycles and Chordless Paths
Ye Xu and Dan Rockmore.
Sparse Coding for Key Node Selection over Networks
Jing Zhao and Shiliang Sun.
Variational Dependent Multi-output Gaussian Process Dynamical Systems