Category Archives: Data Mining

Brief report about DAWAK 2019 / DEXA 2019

Posted on 2019-08-25 by Philippe Fournier-Viger

This week, I am attending the DAWAK 2019 and DEXA 2019 conferences in Linz, Austria from the 26th to the 29th August 2019. In this blog post, I will provide a report about these conferences. About the DAWAK and DEXA conferences DAWAK ( Intern. Conf. on Data Warehousing … Continue reading →

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Funny pictures about data mining / machine learning

Posted on 2019-08-08 by Philippe Fournier-Viger

Today, I will share a few funny pictures related to data mining and machine learning that I have found online. These pictures comes from various sources (I don’t remember who created them). I will also perhaps add more later on that page Associations between … Continue reading →

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Correlation does not imply causation

Posted on 2019-06-10 by Philippe Fournier-Viger

There is a well known principle in statistics that correlation does not imply causation. It means that even if we observe that two variables behave in the same way, we should not conclude that the behavior of one of those variables … Continue reading →

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The review speed of academic journals

Posted on 2019-05-15 by Philippe Fournier-Viger

Today, I will talk about the review speed of academic journals. Review speed is an important criterion for selecting a journal to submit a paper when researchers face time constraints. For example, it is common that some students need to publish a paper quickly … Continue reading →

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MLDM 2019… still not in New York! …and not published by Springer!

Posted on 2019-04-20 by Philippe Fournier-Viger

A few years ago, I decided to give a try at the MLDM 2016 conference, which I had never attended. It was not a bad conference, although quite small and the registration is quite expensive for a conference (about 650 euros). I submitted … Continue reading →

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(video) Mining Frequent Itemsets with the Apriori algorithm

Posted on 2019-04-20 by Philippe Fournier-Viger

This is a video presentation of the Apriori algorithm for discovering frequent itemsets in data. Frequent itemset mining is one of the most popular data mining task. VIDEO LINK: https://www.philippe-fournier-viger.com/spmf/videos/apriori.mp4 The Java source code of the Apriori algorithm and datasets for evaluating its performance are available in the SPMF software. If you want … Continue reading →

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The PAKDD 2019 conference (a brief report)

Posted on 2019-04-12 by Philippe Fournier-Viger

This year, I am attending the PAKDD 2019 conference (23rd Pacific Asia Conference on Knowledge Discovery and Data Mining), in Macau, China, from the 14th to the 17th April 2019. In this blog post, I will provide information about the conference. About the PAKDD conference PAKDD is one of the most important … Continue reading →

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The best data mining mailing lists (for researchers)

Posted on 2019-03-17 by Philippe Fournier-Viger

Today, I will list a few useful mailing lists related to data mining and big data. Subscribing to these mailing list is useful for PhD students and researchers, as many jobs, conferences, special issues and other opportunities are advertised on these mailing lists. It is … Continue reading →

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Analyzing the source code of SPMF (5 years later)

Posted on 2019-01-12 by Philippe Fournier-Viger

Five years ago, I had analyzed the source code of the SPMF data mining software using an open-source tool called CodeAnalyzer ( http://sourceforge.net/projects/codeanalyze-gpl/ ). This had provided some interesting insights about the structure of the project, especially in terms of lines of codes and code to … 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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