Tag Archives: pattern mining

(video) Identifying Stable Periodic Frequent Patterns using SPP-Growth

Posted on 2020-03-01 by Philippe Fournier-Viger

Today, I present a video about finding stable periodic patterns in data, and discuss a new algorithm named SPP-Growth for this task. VIDEO LINK: https://www.philippe-fournier-viger.com/spmf/videos/SPPGrowth.mp4 The  SPP-Growth algorithm and datasets for evaluating its performance are available in the SPMF software, which is open-source and programmed in Java. Source code and … Continue reading →

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The SPMF data mining library v.2.40 is released!

Posted on 2019-10-23 by Philippe Fournier-Viger

Hi all, I am please to announce that a new version of SPMF has just been published (v 2.40). It contains 9 novel algorithms: It also includes some bug fixes and other minor improvements. I did not release a new version of SPMF since a few … Continue reading →

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25 years of pattern mining

Posted on 2019-09-02 by Philippe Fournier-Viger

This year, we are in 2019, and it is already 25 years since Agrawal wrote his seminal papers on frequent itemset mining and association rule mining in 1994. Since then, there has been thousands of papers published on this topic, some about algorithm design, new pattern mining … Continue reading →

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(video) Mining Sequential Rules with RuleGrowth

Posted on 2018-12-26 by Philippe Fournier-Viger

This is a video presentation of the paper “Mining Partially-Ordered Sequential Rules Common to Multiple Sequences” about discovering sequential rules in sequences using the RuleGrowth algorithm. VIDEO LINK: https://www.philippe-fournier-viger.com/spmf/videos/rulegrowth.mp4 More information about the RuleGrowth algorithm are provided in this research paper: Fournier-Viger, P., Wu, C.-W., Tseng, V.S., Cao, L., Nkambou, R. (2015). Mining Partially-Ordered Sequential Rules Common to Multiple … Continue reading →

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(video) Minimal Correlated High Utility Itemsets with FCHM

Posted on 2018-12-20 by Philippe Fournier-Viger

This is a video presentation of the paper “Mining Correlated High-Utility Itemsets Using the bond Measure” about correlated high utility pattern mining using FCHM.  VIDEO LINK: https://www.philippe-fournier-viger.com/spmf/videos/FCHM_correlated_itemsets.mp4 More information about the FCHM algorithm are provided in this research paper: Fournier-Viger, P., Zhang, Y., Lin, J. C.-W., … Continue reading →

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(video) Minimal High Utility Itemset Mining with MinFHM

Posted on 2018-10-22 by Philippe Fournier-Viger

This is a video presentation of the paper “Mining Minimal High Utility Itemsets” about high utility itemset mining using MinFHM. It is the first video of a series of videos that will explain various data mining algorithms. VIDEO LINK : https://www.philippe-fournier-viger.com/spmf/videos/minfhm.mp4 More information … Continue reading →

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The future of pattern mining

Posted on 2018-08-10 by Philippe Fournier-Viger

In this blog post, I will talk about the future of research on pattern mining. I will also discuss some lessons learnt from the decades of research in this field and talk about research opportunities. What is the state of research on pattern mining? Over the last … Continue reading →

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How to run SPMF without installing Java?

Posted on 2018-04-02 by Philippe Fournier-Viger

The SPMF data mining software is a popular open-source software for discovering patterns in data and for performing other data mining tasks. Typically, to run SPMF, Java must have been installed on a computer. However, it is possible to run SPMF on a computer that does not have Java installed. For example, … Continue reading →

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On the Completeness of the CloSpan and IncSpan algorithms

Posted on 2018-01-31 by Philippe Fournier-Viger

In this blog post, I will briefly discuss the fact that the popular CloSpan algorithm for frequent sequential pattern mining is an incomplete algorithm.  This means that in some special situations, CloSpan does not produce the expected results that it has been designed for, and in particular some patterns are … Continue reading →

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On the correctness of the FSMS algorithm for frequent subgraph mining

Posted on 2018-01-20 by Philippe Fournier-Viger

In this blog post, I will explain why the FSMS algorithm for frequent subgraph mining is an incorrect algorithm.  I will publish this blog post because I have found that the algorithm is incorrect after spending a few days to implement the algorithm in 2017 and wish to save time to other researchers … Continue reading →

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