%0 Journal Article %1 Bottcher:2008:EPT:1540276.1540278 %A Böttcher, Mirko %A Höppner, Frank %A Spiliopoulou, Myra %C New York, NY, USA %D 2008 %I ACM %J SIGKDD Explor. Newsl. %K kmd %N 2 %P 3--11 %R 10.1145/1540276.1540278 %T On Exploiting the Power of Time in Data Mining %U http://doi.acm.org/10.1145/1540276.1540278 %V 10 %X We introduce the new paradigm of Change Mining as data mining over a volatile, evolving world with the objective of understanding change. While there is much work on incremental mining and stream mining, both focussing on the adaptation of patterns to a changing data distribution, Change Mining concentrates on understanding the changes themselves. This includes detecting when change occurs in the population under observation, describing the change, predicting change and pro-acting towards it. We identify the main tasks of Change Mining and discuss to what extent they are already present in related research areas. We elaborate on research results that can contribute to these tasks, giving a brief overview of the current state of the art and identifying open areas and challenges for the new research area.

@article{Bottcher:2008:EPT:1540276.1540278, abstract = {We introduce the new paradigm of Change Mining as data mining over a volatile, evolving world with the objective of understanding change. While there is much work on incremental mining and stream mining, both focussing on the adaptation of patterns to a changing data distribution, Change Mining concentrates on understanding the changes themselves. This includes detecting when change occurs in the population under observation, describing the change, predicting change and pro-acting towards it. We identify the main tasks of Change Mining and discuss to what extent they are already present in related research areas. We elaborate on research results that can contribute to these tasks, giving a brief overview of the current state of the art and identifying open areas and challenges for the new research area.}, acmid = {1540278}, added-at = {2014-06-20T13:56:20.000+0200}, address = {New York, NY, USA}, author = {B\"{o}ttcher, Mirko and H\"{o}ppner, Frank and Spiliopoulou, Myra}, biburl = {https://www.bibsonomy.org/bibtex/29b7594e69f98f15593e8beba821f4d91/kmd-ovgu}, doi = {10.1145/1540276.1540278}, interhash = {0d20c0d555267590e76835008aa56309}, intrahash = {9b7594e69f98f15593e8beba821f4d91}, issn = {1931-0145}, issue_date = {December 2008}, journal = {SIGKDD Explor. Newsl.}, keywords = {kmd}, month = dec, number = 2, numpages = {9}, pages = {3--11}, publisher = {ACM}, timestamp = {2014-06-20T13:56:20.000+0200}, title = {On Exploiting the Power of Time in Data Mining}, url = {http://doi.acm.org/10.1145/1540276.1540278}, volume = 10, year = 2008 }