Tag Archives: data mining

Skills needed for a data scientists? (comments on the HBR article)

Posted on 2018-10-26 by Philippe Fournier-Viger

Recently, I have read an article of the Harvard Business Review (HBR) website about data sciences skills for businesses. This article proposes to categorize skills related to data on a 2×2 matrix where skills are labelled as useful VS not useful, and … Continue reading →

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Report about the DEXA 2018 and DAWAK 2018 conferences

Posted on 2018-09-06 by Philippe Fournier-Viger

This week, I am attending the DEXA 2018 (29th International Conference on Database and Expert Systems Applications) and the DAWAK 2018 (20th Intern. Conf. on Data Warehousing and Knowledge Discovery) conferences from the 3rd to 6th September in Regensburg, Germany. Those two conferences are well established European conferences dedicated mainly to research on database and data mining. These conferences are always collocated. … Continue reading →

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Report about the KDD 2018 conference

Posted on 2018-08-20 by Philippe Fournier-Viger

This week, I am participating to the KDD 2018 ( 24th ACM SIGKDD Intern. Conference on Knowledge Discovery and Data Mining), in London, UK from the 19th to 23rd August 2018. The KDD conference is an international conference, established 24 years ago. It is the top conference in the field of data mining / … 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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An interview with P. Fournier-Viger about AI and data mining

Posted on 2018-08-02 by Philippe Fournier-Viger

I recently was interviewed by Djavan de Clercq, a graduate student from Tsinghua University, working on Machine Learning and Optimization. The interview can be read here (on LinkedIn).   I answer ten questions related to data mining and AI research. —-Philippe Fournier-Viger is a professor of Computer Science and also the founder of the open-source data mining software SPMF, offering … Continue reading →

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A Model for Football Pass Prediction (source code + dataset)

Posted on 2018-08-01 by Philippe Fournier-Viger

In this blog post, I will discuss the data challenge of the Machine Learning for Sport Analytics workshop (MLSA 2018) at PKDD 2018. The challenge consisted of predicting the receivers of football passes (pass prediction). I will first briefly describe the data and then … Continue reading →

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IEA AIE 2018 conference (a brief report)

Posted on 2018-06-30 by Philippe Fournier-Viger

This week, I am attending the IEA AIE 2018 conference ( 31st International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems) in Montreal, Canada. About the conference The IEA AIE conference is an international conference on artificial intelligence and related topics. Conference opening On Tuesday morning, it was the conference opening. This year,  146 papers … Continue reading →

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PAKDD 2018 Conference (a brief report)

Posted on 2018-06-01 by Philippe Fournier-Viger

In this blog post, I will discuss the PAKDD 2018 conference (Pacific Asia Conference on Knowledge Discovery and Data Mining), in Melbourne Australia, from the 3rd June to the 6th June 2018. About the PAKDD conference PAKDD is an important conference in the data science / data mining research community, mainly attended by researchers from … 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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Subgraph mining datasets

Posted on 2018-02-14 by Philippe Fournier-Viger

In this post, I will provide links to standard benchmark datasets that can be used for frequent subgraph mining. Moreover, I will provide a set of small graph datasets that can be used for debugging subgraph mining algorithms. The format of graph datasets A graph dataset is a text … Continue reading →

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