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**:

- the
**HUIM-ABC**algorithm for**mining**high utility itemsets using Artificial Bee Colony Optimization (thanks to Wei Song and Chaoming Huang for contributing the code) - the
**TKG****algorithm**for**mining**the top-k frequent subgraphs in a graph database (thanks to Fournier-Viger, P. and Chao Cheng) - the
**gSpan**algorithm for**mining**the frequent subgraphs in a graph database (thanks to Chao Cheng) - the
**SPP-Growth**algorithm for**mining**stable periodic itemsets in a transaction database (by Peng Yang) - the
**MPFPS-BFS algorithm**for**mining**periodic patterns common to multiple sequences (by Zhitian Li). - the
**MPFPS-DFS algorithm**for**mining**periodic patterns common to multiple sequences (by Zhitian Li). - the
**NAFCP algorithm**for**mining**frequent closed itemsets (thanks to Nader Aryabarzan et al.) - the
**OPUS-Miner**algorithm for**mining**self-sufficient itemsets (thanks to Xiang Li for converting the original C++ code to Java)

It also includes some bug fixes and other minor improvements.

I did not release a new version of **SPMF **since a few months because I was quite busy recently. But the **SPMF **project is still very active. I am currently working on preparing a few more algorithms for release. I will try to make the next release in November.

Also I would like to say thanks again to all the persons who have contributed, used, cited, and supported the software! This is really helpful! Moreover, all contributions are always welcome.

—**Philippe Fournier-Viger** is a professor of Computer Science and also the founder of the open-source **data** **mining** software **SPMF**, offering more than 150 **data** **mining** algorithms.