Michael Hahsler

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Thomas ReuttererWU Vienna University of Economics and BusinessEmail verificata su wu.ac.at
Matt PiekenbrockNortheastern University - Khoury College of Computer SciencesEmail verificata su northeastern.edu
Bettina GrünWirtschaftsuniversität WienEmail verificata su wu.ac.at
Anurag NagarUniversity of Texas at DallasEmail verificata su utdallas.edu
Jake DrewPostdoctoral Fellow - Darwin Deason Institute for Cyber Security, SMUEmail verificata su mail.smu.edu
Eli OlinickSouthern Methodist UniversityEmail verificata su lyle.smu.edu
Paul S. KruegerUniversity of North TexasEmail verificata su unt.edu
Derek DoranDirector of Research, Tenet3; Associate Professor of Computer Science & Engineering, Wright StateEmail verificata su wright.edu
Tyler MooreTandy Professor of Cyber Security and Information Assurance, University of TulsaEmail verificata su utulsa.edu
Stefan KochProfessor of Information Systems - Information Engineering, Johannes Kepler University LinzEmail verificata su jku.at
Sheila H. WilliamsEmail verificata su smu.edu
Lars Schmidt-ThiemeUniversity of Hildesheim, GermanyEmail verificata su ismll.uni-hildesheim.de
Monnie McGeeSouthern Methodist UniversityEmail verificata su smu.edu
Eric C. LarsonAssociate Professor, Computer Science, Southern Methodist UniversityEmail verificata su smu.edu
Tomáš KliegrVysoká škola ekonomická v PrazeEmail verificata su vse.cz
Jaroslav KuchařFaculty of Information Technology, Czech Technical University in PragueEmail verificata su fit.cvut.cz
Hossein KamalzadehPh.D., OREM Department, Southern Methodist UniversityEmail verificata su smu.edu
Mehmet U S AyvaciAssociate Professor, Jindal School of Management at University of Texas at DallasEmail verificata su utdallas.edu
Bekir Tanriover, MD, MPH, MBA, FASTUniversity of Arizona, COM -TucsonEmail verificata su email.arizona.edu
Hadil ShaibaPrincess Nourah bint Abdulrahman UniversityEmail verificata su pnu.edu.sa

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Michael Hahsler

Associate Professor, Computer Science, Southern Methodist University

Email verificata su lyle.smu.edu - Home page

Artificial Intelligence Machine Learning Data mining Combinatorial Optimization


Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
A review of methods for measuring willingness-to-pay C Breidert, M Hahsler, T Reutterer Innovative Marketing 2 (4), 8-32, 2006	937	2006
A computational environment for mining association rules and frequent item sets M Hahsler, B Grün, K Hornik Journal of Statistical Software 14 (15), 1-25, 2005	702	2005
dbscan: Fast Density-based Clustering with R M Hahsler, M Piekenbrock, D Doran Journal of Statistical Software 91 (1), 1-30, 2019	668	2019
Getting things in order: an introduction to the R package seriation M Hahsler, K Hornik, C Buchta Journal of Statistical Software 25 (3), 1-34, 2008	297	2008
arules: Mining Association Rules and Frequent Itemsets M Hahsler, C Buchta, B Gruen, K Hornik Comprehensive R Archive Network, 2005	296*	2005
TSP-Infrastructure for the traveling salesperson problem M Hahsler, K Hornik Journal of Statistical Software 23 (2), 1-21, 2007	279	2007
The arules R-package ecosystem: analyzing interesting patterns from large transaction data sets M Hahsler, S Chelluboina, K Hornik, C Buchta The Journal of Machine Learning Research 12, 2021-2025, 2011	191	2011
arulesViz: Visualizing Association Rules and Frequent Itemsets M Hahsler, S Chelluboina Comprehensive R Archive Network, 2011	182*	2011
Visualizing association rules in hierarchical groups M Hahsler, R Karpienko Journal of Business Economics 87 (3), 317-335, 2017	175	2017
Clustering data streams based on shared density between micro-clusters M Hahsler, M Bolanos IEEE Transactions on Knowledge and Data Engineering 99 (99), 1-14, 2016	157	2016
recommenderlab: An R Framework for Developing and Testing Recommendation Algorithms M Hahsler arXiv preprint arXiv:2205.12371, 2022	116	2022
Density-based clustering of applications with noise (DBSCAN) and related algorithms M Hahsler, M Piekenbrock Comprehensive R Archive Network, 2019	103*	2019
A probabilistic comparison of commonly used interest measures for association rules M Hahsler https://mhahsler.github.io/arules/docs/measures, 2015	95*	2015
SOStream: Self organizing density-based clustering over data stream C Isaksson, MH Dunham, M Hahsler International workshop on machine learning and data mining in pattern …, 2012	89	2012
New probabilistic interest measures for association rules M Hahsler, K Hornik Intelligent Data Analysis 11 (5), 437-455, 2007	84	2007
Implications of probabilistic data modeling for mining association rules M Hahsler, K Hornik, T Reutterer From Data and Information Analysis to Knowledge Engineering: Proceedings of …, 2006	82	2006
arulesViz: interactive visualization of association rules with R M Hahsler The R Journal 9 (2), 2017	79	2017
Polymorphic malware detection using sequence classification methods J Drew, T Moore, M Hahsler 2016 IEEE Security and Privacy Workshops (SPW), 81-87, 2016	69	2016
Evaluation of recommender algorithms for an internet information broker based on simple association rules and on the repeat-buying theory A Geyer-Schulz, M Hahsler proceedings WEBKDD, 100-114, 2002	69	2002
Polymorphic malware detection using sequence classification methods and ensembles: BioSTAR 2016 Recommended Submission-EURASIP Journal on Information Security J Drew, M Hahsler, T Moore EURASIP Journal on Information Security 2017, 1-12, 2017	68	2017

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