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Category Archives: Data science
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
Analyzing the COVID-19 genome with AI and data mining techniques (paper + data + code)
Recently, my team has been working on analyzing COVID-19 genome sequences using pattern mining and other AI techniques. We have recently published a paper in the Applied Intelligence journal about this. In this blog post, I will give some brief … 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 open-source 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, open-source, Pattern Mining, Utility Mining
Tagged algorithm, data mining, data science, dataset, open source, open-source, pattern mining, spmf
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Analyzing COVID-19 tweets to understand the public opinion
In this blog post, I will talk briefly about how tweets collected on Twitter can be analyzed to understand the public opinion about COVID-19. This is based on the below research paper, that I have recently participated to: Noor, S., … Continue reading
Posted in artificial intelligence, Data Mining, Data science
Tagged coronavirus, covid, covid19, tweet, twitter
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Discovering Alarm Correlation Rules for Network Fault Management (video)
In this blog post, I will share the video of our new paper about analyzing alarms in telecomunication networks presented at the AIOPS 2020 workshop. This work is part of an industrial collaboration project. The motivation for this project is … Continue reading
Posted in Data Mining, Data science, Video
Tagged alarm, network, pattern mining, rules, telecommunication network
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The 10 most cited papers in our “Data Science and Pattern Recognition” journal!
As some of you know, I am editor-in-chief of the Data Science and Pattern Recognition (DSPR) journal. This journal has started in 2017 and four volumes have been published already with 28 papers, which I consider as a success. One … Continue reading
Posted in Academia, Big data, cfp, Data science, General, Machine Learning
Tagged big data, data mining, data science, dspr, journal, kdd, pattern recognition
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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 co-organizing at the IEEE ICDM 2020 conference. This workshop was previously held at KDD 2018 and … Continue reading
Datasets of 30 English novels for pattern mining and text mining
Today, I want to announce that I have just made public datasets of 30 novels from English Novels from 10 authors of the XIX century. These datasets can be used for testing algorithms for sequential pattern mining, sequential rule mining, as well as for some text … Continue reading
The PAKDD 2020 conference (a brief report)
In this report, I will talk about the 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2020), from the 11th to 14th May 2020. The PAKDD conference PAKDD is a top international conference on data mining / big data in the Pacific-Asia part of the world. … Continue reading
Posted in Conference, Data Mining, Data science
Tagged conference, data mining, data science, pakdd
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“Pattern Mining :Theory and Practice” (textbook in Thai, with SPMF)
Hi all, this is to announce that a new textbook in Thai has been published about pattern mining, which includes many examples using the SPMF software. The textbook named “Pattern Mining: Theory and Practice” is written by teacher Panida Songram from Mahasarakham University (Thailand) and can be used for … Continue reading
Posted in Data Mining, Data science, Pattern Mining
Tagged pattern mining, textbook, thai
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