Pattern Mining in Sparse Temporal Domains, an Interpolation Approach
C. Pölitz.. Proceedings of LWA2010 - Workshop-Woche: Lernen, Wissen & Adaptivitaet, Kassel, Germany, (2010)
Abstract
Weblog systems, mobile phone companies or GPS devices collect large amounts of personalized data including temporal, positional and textual information. Patterns extracted from such data can give insight in the behavior and mood of people. These patterns are often imprecise due to sparseness in the data. We propose an interpolation technique that augments local patterns with elements that seem to be locally unimportant but with global information they are interesting.
%0 Conference Paper
%1 kdml9
%A Pölitz., Christian
%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 data mining pattern room:0410 sequential session:poster sparse temporal workshop:kdml
%T Pattern Mining in Sparse Temporal Domains, an Interpolation Approach
%U http://www.kde.cs.uni-kassel.de/conf/lwa10/papers/kdml9.pdf
%X Weblog systems, mobile phone companies or GPS devices collect large amounts of personalized data including temporal, positional and textual information. Patterns extracted from such data can give insight in the behavior and mood of people. These patterns are often imprecise due to sparseness in the data. We propose an interpolation technique that augments local patterns with elements that seem to be locally unimportant but with global information they are interesting.
@inproceedings{kdml9,
abstract = {Weblog systems, mobile phone companies or GPS devices collect large amounts of personalized data including temporal, positional and textual information. Patterns extracted from such data can give insight in the behavior and mood of people. These patterns are often imprecise due to sparseness in the data. We propose an interpolation technique that augments local patterns with elements that seem to be locally unimportant but with global information they are interesting.},
added-at = {2010-10-05T14:15:12.000+0200},
address = {Kassel, Germany},
author = {Pölitz., Christian},
biburl = {https://www.bibsonomy.org/bibtex/228b90e4fc0f85e06475433f669b9ba15/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 = {11344b93df4a11d9f1c05c40ffaa76be},
intrahash = {28b90e4fc0f85e06475433f669b9ba15},
keywords = {data mining pattern room:0410 sequential session:poster sparse temporal workshop:kdml},
presentation_end = {2010-10-05 17:05:00},
presentation_start = {2010-10-05 16:55:00},
room = {0410},
session = {poster},
timestamp = {2010-10-05T14:15:14.000+0200},
title = {Pattern Mining in Sparse Temporal Domains, an Interpolation Approach},
track = {kdml},
url = {http://www.kde.cs.uni-kassel.de/conf/lwa10/papers/kdml9.pdf},
year = 2010
}