Archives
Categories
- Academia (91)
- artificial intelligence (35)
- Big data (83)
- Bioinformatics (7)
- cfp (13)
- China (1)
- Chinese posts (1)
- Conference (78)
- Data Mining (190)
- Data science (107)
- Database (2)
- General (43)
- Industry (2)
- Java (13)
- Latex (12)
- Machine Learning (22)
- Mathematics (2)
- open-source (44)
- Other (4)
- Pattern Mining (94)
- Plagiarism (1)
- Programming (17)
- Research (108)
- spmf (63)
- Time series (3)
- Uncategorized (30)
- Utility Mining (23)
- Video (19)
- Website (6)
-
Recent Posts
- An EXE version of SPMF for Windows
- A First Release of SPMF-Server and SPMF-Server Clients
- CFP: Special session at SOMET 2026
- SPMF 2.65 is released!
- The Item-Itemset Matrix Viewer: a new feature in SPMF 2.65 (to be released)
- Merry X-Mas and Happy New year to SPMF users!
- The 1st HP4MoDa workshop was held at BIBM 2025
- Another release of SPMF: v2.64b
- A prototype of an improved GUI for the SPMF pattern mining software
- Upcoming in SPMF 2.64b : The “Pattern Diff Analyzer”
Recent Comments


-

-


Tag cloud
- academia
- ai
- algorithm
- apriori
- article
- artificial intelligence
- association rule
- big data
- cfp
- china
- conference
- data
- data mining
- data science
- graph
- high utility itemset mining
- icdm
- itemset
- itemset mining
- java
- journal
- latex
- machine learning
- open-source
- open source
- pakdd
- paper
- papers
- pattern
- pattern mining
- periodic pattern
- phd
- Research
- researcher
- reviewer
- sequence
- sequential pattern
- software
- spmf
- udml
- utility mining
- video
- website
- workshop
- writing
Number of visitors:
2,778,601
Author Archives: Philippe Fournier-Viger
The 7th China International Technology Expo – CITE 2019 (a brief report)
This week, I have attended the 7th China International Technology Expo (CITE 2019), which was held at the Shenzhen Convention and Exhibition Center in the city of Shenzhen, China from the 9th to the 11th April 2019. In this blog post, I will give a brief overview of this fair, where various companies were showing … Continue reading
The best data mining mailing lists (for researchers)
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
Posted in Big data, Data Mining, Data science
Tagged big data, data, data mining, data science, machine learning, mailing list, Research
Leave a comment
Analyzing the source code of SPMF (5 years later)
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
Posted in Data Mining, Data science, open-source, spmf
Tagged data analysis, data mining, data science, open source, software, spmf
Leave a comment
How to improve the quality of your research papers?
In this blog post, I talk about how to improve the quality of your research papers. This is an important topic as most researchers aim at publishing papers in top level conferences and journals for various reasons such as graduating, obtaining a promotion or securing funding. … Continue reading
(video) Mining Sequential Rules with RuleGrowth
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
Posted in Big data, Data Mining, Pattern Mining
Tagged data mining, data science, pattern mining, sequence, sequential rule
Leave a comment
Report about the 2018 International Workshop on Mining of Massive Data and IoT
This week, I have attended the 2018 International Workshop on Mining of Massive Data and IoT (2018 年大数据与物联网挖掘国际研讨会) organized by the Fujian Normal University in the city of Fuzhou, China from the 18th to 20thDecember 2018. I have attended the workshop to give a talk … Continue reading
Posted in Conference, Data Mining, Data science
Tagged data mining, fuzhou, massive data, workshop
Leave a comment
(video) Minimal Correlated High Utility Itemsets with FCHM
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
Posted in Big data, Data Mining, Data science, Video
Tagged big data, data, data science, high utility itemset, high utility mining, pattern mining
Leave a comment
Report about the ICGEC 2018 conference
I have recently attended the ICGEC 2018 conference (12th International Conference on Genetic and Evolutionary Computing) from December 14-17, 2018 in Changzhou, China. In this blog post, I will describe activities that I have attended at the conference. About the ICGEC conference IGCEC is … Continue reading
Introduction to frequent subranking mining
Rankings are made in many fields, as we naturally tend to rank objects, persons or things, in different contexts. For example, in a singing or a sport competition, some judges will rank participants from worst to best and give prizes to … Continue reading
Posted in Big data, Data Mining, Data science, Pattern Mining
Tagged data, data mining, data science, pattern, sequential pattern
Leave a comment
Is the next artificial intelligence winter coming?
In recent years, there have been an increased interest in Artificial Intelligence (AI). This is due in part to some advances for training and building neural networks, which have allowed to solve some difficult problems with greater success. This has lead … Continue reading