Albrecht Zimmermann's papers

Papers

One-stop shop for my papers. This is mainly meant to augment my Google Scholar and DBLP entries with non-publisher versions of the papers. For brevity, I only list title and where it was published; full information – in particular the names of my invaluable co-authors – is contained in the linked BibTex files. Notably, not everything on here is actually formally published.

Journal publications

• Towards a Partial Order Graph for Interactive Pharmacophore Exploration: Extraction of Pharmacophores Activity Delta in Journal of Cheminformatics
• New Pharmacophore Fingerprints and Weight-matrix Learning for Virtual Screening. Application to Bcr-Abl Data in Molecular Informatics
• LPbyCD: a new scalable and interpretable approach for Link Prediction via Community Detection in bipartite networks in Applied Network Science
• Mining communities and their descriptions on attributed graphs: a survey in Machine Learning
• Method Evaluation, Parametrization, and Result Validation in Unsupervised Data Mining: A Critical Survey in WIREs Data Mining and Knowledge Discovery
• Exceptional contextual subgraph mining in Machine Learning
• Basketball predictions in the NCAAB and NBA: Similarities and differences in Statistical Analysis and Data Mining
• The data problem in data mining in SIGKDD Explorations 16 (2)
• Understanding episode mining techniques: Benchmarking on diverse, realistic, artificial data in Intelligent Data Analysis 18(5)
• Objectively evaluating condensed representations and interestingness measures for frequent itemset mining in Journal of Intelligent Information Systems
• One In A Million: Picking The Right Patterns in Knowledge and Information Systems 18(1)
• Cluster-Grouping: From Subgroup Discovery to Clustering in Machine Learning 77(1)

Publications in international, peer-reviewed conferences, and workshops with official proceedings

• Learning predictive models for match outcomes in US sports, and using them to bet in Sports Analytics. ISACE 2024.
• Chance and the predictive limit in basketball (both college and professional) in DS 2023
• Selecting Outstanding Patterns Based on Their Neighbourhood in IDA 2022
• Using Data Science to Improve the Identification of Plant Nutritional Status in DSAA'20
• A Relaxation-Based Approach for Mining Diverse Closed Patterns in ECML PKDD 2020
• PrePeP: A Light-Weight, Extensible Tool for Predicting Frequent Hitters. in ECML PKDD 2020
• Link prediction via community detection in bipartite multi-layer graphs in SAC 2020
• Link Prediction in Multi-layer Networks and Its Application to Drug Design in IDA 2018
• PrePeP: A Tool for the Identification and Characterization of Pan Assay Interference Compounds in KDD 2018
• An Experimental Approach For Information Extraction in Multi-Party Dialogue Discourse in CICLing 2018
• Integer Linear Programming for Pattern Set Mining; with an Application to Tiling in PAKDD 2017
• Efficiently Finding Conceptual Clustering Models with Integer Linear Programming in IJCAI 2016
• Gazouille: Detecting and Illustrating Local Events from Geolocalized Social Media Streams in ECML/PKDD 2015
• Detecting marginal and conditional independencies between events and learning their causal structure. in ECSQARU 2013
• Objectively evaluating interestingness measures for frequent itemset mining in Trends and Applications in Knowledge Discovery and Data Mining 2013
• Generating Diverse Realistic Data Sets for Episode Mining in Data Mining Workshops 2012
• Declarative Heuristic Search for Pattern Set Mining in Data Mining Workshops 2011
• Fast, Effective Molecular Feature Mining by Local Optimization in ECML/PKDD 2010 (3)
• Aggregated Subset Mining in PAKDD 2009
• Ensemble-Trees: Leveraging Ensemble Power inside Decision Trees in Discovery Science 2008
• The Chosen Few: On Identifying Valuable Patterns in ICDM 2007
• Constraint-Based Pattern Set Mining in SDM 2007
• Don't Be Afraid of Simpler Patterns in PKDD 2006
• CTC - Correlating Tree Patterns for Classification in ICDM 2005
• Tree² - Decision Trees for Tree Structured Data in PKDD 2005
• Inductive Querying for Discovering Subgroups and Clusters in Constraint-Based Mining and Inductive Databases
• CorClass: Correlated Association Rule Mining for Classification in Discovery Science 2004

Edited volumes/proceedings

• Machine Learning and Data Mining for Sports Analytics 2022 at Springer Link
• Machine Learning and Data Mining for Sports Analytics 2021 at Springer Link
• ECML PKDD 2020 Workshops at Springer Link
• Machine Learning and Data Mining for Sports Analytics 2020 at Springer link
• 1st Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning (EDML 2019) at CEUR-WS
• Machine Learning and Data Mining for Sports Analytics 2018 at Springer link
• Machine Learning and Data Mining for Sports Analytics 2017 at CEUR-WS
• Machine Learning and Data Mining for Sports Analytics 2015 at CEUR-WS
• Machine Learning and Data Mining for Sports Analytics 2013 at CEUR-WS

Book chapters

• Constraint-based Pattern Mining in Frequent Pattern Mining
• Supervised Pattern Mining and Applications to Prediction in Frequent Pattern Mining
• From Local Patterns to Classification Models in Inductive Databases and Constraint-Based Mining

Invited contributions

• Using machine learning to assess and compare athletes in team sports, keynote at PACSS/IACSS 2021

Workshops without official publications, technical reports, and preprints

• What can connectivity characteristics of networks tell us about the quality of link predictions? in GEM 2019
• Wages of wins: could an amateur make money from match outcome predictions? in MLSA16
• Exploring chance in NCAA basketball in MLSA15
• Profiling Users of the Velo'v Bike Sharing System in MUD@ICML 2015
• Exploring the efficacy of molecular fragments of different complexity in computational SAR modeling, Preprint on arXiv
• A feature construction framework based on outlier detection and discriminative pattern mining, Preprint on arXiv
• MLSA13 - Proceedings of "Machine Learning and Data Mining for Sports Analytics", workshop @ ECML/PKDD 2013, Technical Report
• Predicting NCAAB match outcomes using ML techniques – some results and lessons learned in MLSA13 @ ECML/PKDD 2013
• On the search for and appreciation of unexpected results in data mining research (or: Science - we might be doing it wrong) in "The Silver Lining", workshop @ ECML/PKDD 2012
• Pattern-Based Classification: A Unifying Perspective in "From Local Patterns to Global Models", workshop @ ECML/PKDD 2009