The mission of the Journal of Machine Learning Gossip (JMLG) is to provide an archival source of important information that is often discussed informally at conferences but is rarely, if ever, written down.
The Knowledge Discovery Machine Learning (KDML) group focuses on the neighboring subfields of computer science known as knowledge discovery in databases (KDD, sometimes referred to simply as data mining) and machine learning (ML). For us, these fields include on the one hand the automated analysis of large data sets using intelligent algorithms that are capable of extracting from the collected data hidden knowledge in order to produce models that can be used for prediction and decision making. On the other hand, they also include algorithms and systems that are capable of learning from experience and adapting to their environment or their users.
P. Cimiano, and J. Völker. Proceedings of the 10th International Conference on Applications of Natural Language to Information Systems (NLDB), volume 3513 of Lecture Notes in Computer Science, page 227-238. Alicante, Spain, Springer, (June 2005)
J. Tang, H. fung Leung, Q. Luo, D. Chen, and J. Gong. IJCAI'09: Proceedings of the 21st international jont conference on Artifical intelligence, page 2089--2094. San Francisco, CA, USA, Morgan Kaufmann Publishers Inc., (2009)
C. Brewster, F. Ciravegna, and Y. Wilks. NLDB '02: Proceedings of the 6th International Conference on Applications of Natural Language to Information Systems-Revised Papers, page 203--207. London, UK, Springer-Verlag, (2002)