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 SPMF 2.48 + The Pattern Mining Wiki
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 Approximate Algorithms for High Utility Itemset Mining
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Category Archives: Utility Mining
Approximate Algorithms for High Utility Itemset Mining
On this blog, I have previously given an introduction to a popular data mining task called high utility itemset mining. Put simply, this task aims at finding all the sets of values (items) that have a high importance in a … Continue reading
Posted in Pattern Mining, Utility Mining
Tagged bat algorithm, Bpso, genetic algorithm, hill climbing, HUIMGA, itemset mining, pso, simulated annealing, utility mining
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UDML 2021 @ ICDM 2021
Hi all, This is to let you know that the UDML workshop on utility driven mining and learning is back again this year at ICDM, for the fourth edition. The topic of this workshop is the concept of utility in … Continue reading
Posted in Big data, cfp, Conference, Data Mining, Utility Mining
Tagged cfp, data mining, icdm, icdm conference, machine learning, udml, utility mining, workshop
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An Overview of Pattern Mining Techniques
In this blog post, I will give an overview of some of the main pattern mining tasks, to explain what kind of patterns can be found in different types of symbolic data. I will describe some main types of data … Continue reading
New version of SPMF (2.44): 4 new algorithms, datasets and features
Today, I am happy to announce that a new version of the SPMF opensource data mining software is released (v. 2.44). This is the download page. This new version was made possible due to several contributors. What is new? New … Continue reading
Posted in Data Mining, Data science, opensource, Pattern Mining, Utility Mining
Tagged algorithm, data mining, data science, dataset, open source, opensource, pattern mining, spmf
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(video) TopK CrossLevel High Utility Itemset Mining
Today, I will share a video of our upcoming paper presentation about topk crosslevel high utility itemset mining that we will present at the UDML 2020 workshop at ICDM 2020. In this paper, we present a novel algorithm named TKC … Continue reading
Posted in Pattern Mining, Utility Mining, Video
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The Upcoming 3rd Utility Mining and Learning Workshop (UDML 2020!) at IEEE ICDM 2020
Today, I just want to talk a little bit about the upcoming 3rd UDML 2020 workshop on utility mining and learning that I am coorganizing at the IEEE ICDM 2020 conference. This workshop was previously held at KDD 2018 and … Continue reading
Five recent books on pattern mining
In this blog post, I will list a few interesting and recent books on the topic of pattern mining (discovering interesting patterns in data). This mainly lists books from the last 5 years. High utility pattern mining: Theory, Applications and algorithms (2019). This … Continue reading
Posted in Big data, Data Mining, Pattern Mining, Utility Mining
Tagged big data, book, data, data mining, data science, pattern mining
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UDML 2020 – Utility Driven Mining and Learning Workshop
Hi all, This is to let you know the good news that the UDML workshop on Utility Driven Mining and Learning will be back this year, at IEEE ICDM 2020, for the third edition (UDML 2020). This is a good venue to submit your papers about data mining and machine … Continue reading
Posted in Big data, Data Mining, Pattern Mining, Utility Mining
Tagged highutility mining, icdm, pattern mining, udml, utility mining, workshop
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(video) Mining CostEffective Patterns
In this blog post, I will share another talk that I have recorded recently. This time, I will explain a new paper from my team about discovering costeffective patterns using some algorithms called CEPB and CEPN. Mining costeffective patterns is a new topic in pattern mining … Continue reading
Posted in Big data, Data Mining, Pattern Mining, Utility Mining, Video
Tagged cost, pattern mining, sequence, utility mining, video
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Upcoming book: High Utility Itemset Mining: Theory, Algorithms and Applications
I am happy to announce that the draft of the book about high utility pattern mining has been finalized and submitted to the publisher (Springer). It should thus be published in the very near future. The book contains 12 chapters written by several top researchers from … Continue reading