%0 Conference Paper %1 kdml22 %A Umbrich, Jürgen %A Karnstedt, Marcel %A Land., Sebastian %B Proceedings of LWA2010 - Workshop-Woche: Lernen, Wissen & Adaptivitaet %C Kassel, Germany %D 2010 %E Atzmüller, Martin %E Benz, Dominik %E Hotho, Andreas %E Stumme, Gerd %K analysis change data dataset dynamics fourier frequency mining predication room:0446 session:kdml2 workshop:kdml %T Towards Understanding the Changing Web: Mining the Dynamics of Linked-Data Sources and Entities %U http://www.kde.cs.uni-kassel.de/conf/lwa10/papers/kdml22.pdf %X A huge amount of content found on the Web is dynamic by its nature, particularly with the raise of Web 2.0 and beyond. This is of special interest for the Semantic Web community, not only but particularly regarding resources on the Linked Open Data (LOD) Web. However, the dataset dynamics of the LOD graph are nearly unex- plored. Existing approaches from the tradition HTML Web are not sufficient to mine and dis- cover the dynamics with satisfying accuracy and efficiency, as they do not regard the special char- acteristics of LOD. We present first initial results on this topic and discuss future steps. First results are obtained by mining the groups of URIs with similar change frequencies and by applying time series techniques as well as K-Means clustering.

@inproceedings{kdml22, abstract = {A huge amount of content found on the Web is dynamic by its nature, particularly with the raise of Web 2.0 and beyond. This is of special interest for the Semantic Web community, not only but particularly regarding resources on the Linked Open Data (LOD) Web. However, the dataset dynamics of the LOD graph are nearly unex- plored. Existing approaches from the tradition HTML Web are not sufficient to mine and dis- cover the dynamics with satisfying accuracy and efficiency, as they do not regard the special char- acteristics of LOD. We present first initial results on this topic and discuss future steps. First results are obtained by mining the groups of URIs with similar change frequencies and by applying time series techniques as well as K-Means clustering.}, added-at = {2010-10-05T14:15:12.000+0200}, address = {Kassel, Germany}, author = {Umbrich, Jürgen and Karnstedt, Marcel and Land., Sebastian}, biburl = {https://www.bibsonomy.org/bibtex/250b573c8fd140917780dd7514bb04e9f/lwa2010}, booktitle = {Proceedings of LWA2010 - Workshop-Woche: Lernen, Wissen {\&} Adaptivitaet}, crossref = {lwa2010}, editor = {Atzmüller, Martin and Benz, Dominik and Hotho, Andreas and Stumme, Gerd}, interhash = {45a602fb949beb56b5c94d47ee45f54d}, intrahash = {50b573c8fd140917780dd7514bb04e9f}, keywords = {analysis change data dataset dynamics fourier frequency mining predication room:0446 session:kdml2 workshop:kdml}, presentation_end = {2010-10-05 17:35:00}, presentation_start = {2010-10-05 17:25:00}, room = {0446}, session = {kdml2}, timestamp = {2010-10-05T14:15:13.000+0200}, title = {Towards Understanding the Changing Web: Mining the Dynamics of Linked-Data Sources and Entities}, track = {kdml}, url = {http://www.kde.cs.uni-kassel.de/conf/lwa10/papers/kdml22.pdf}, year = 2010 }