A current publication of the Institute for Web Science and Technologies and the Institute for Computer Science at the University of Koblenz-Landau was accepted as a "full paper“ at the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. The paper is the result of a cooperation with GESIS and the University of Würzburg was well as the Technical University Graz.
The paper presents a new method for analysing sequential data. Possible applications include studying human mobility or analyzing the behavior of internet users. The value of the approach has been demonstrated by synthetic datasets as well as social media data of flickr and last.fm.
The International Conference on Knowledge Discovery and Data Mining is the leading data science conference. With an acceptance rate of only 8.9% it is extremely competitive.
- Publication reference:
- Florian Lemmerich, Martin Becker, Philipp Singer, Denis Helic, Andreas Hotho and Markus Strohmaier, Mining Subgroups with ExceptionalTransition Behavior, 22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining, San Francisco, USA, 2016. URL: http://www.kdd.org/kdd2016/papers/files/Paper_185.pdf