<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Publication on Kai Kunze</title><link>https://kaikunze.de/categories/publication/</link><description>Recent content in Publication on Kai Kunze</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Mon, 09 Jul 2012 00:00:00 +0000</lastBuildDate><atom:link href="https://kaikunze.de/categories/publication/index.xml" rel="self" type="application/rss+xml"/><item><title>Towards Dynamically Configurable Context Recognition Systems</title><link>https://kaikunze.de/2012/07/09/draft-version-of-aaai-workshop-paper-online/</link><pubDate>Mon, 09 Jul 2012 00:00:00 +0000</pubDate><guid>https://kaikunze.de/2012/07/09/draft-version-of-aaai-workshop-paper-online/</guid><description>&lt;p&gt;Here&amp;rsquo;s a &lt;a href="https://kaikunze.de/papers/pdf/kunze2012towards.pdf"&gt;draft version of my publication&lt;/a&gt; for the &lt;a href="http://activitycontext.org/"&gt;Activity Context Workshop&lt;/a&gt;&#10;in Toronto. Bellow the abstract.&lt;/p&gt;&#10;&lt;p&gt;Here&amp;rsquo;s the link to the &lt;a href="https://github.com/kkai/snsrlog"&gt;source code for snsrlog for iPhone&lt;/a&gt; (which I mentioned during my talk).&lt;/p&gt;&#10;&lt;hr&gt;&#10;&lt;p&gt;Abstract&lt;/p&gt;&#10;&lt;p&gt;General representation, abstraction and exchange definitions are crucial for dynamically configurable context recognition.&#10;However, to evaluate potential definitions, suitable standard datasets are needed.&#10;This paper presents our effort to create and maintain large scale, multimodal standard datasets&#10;for context recognition research. We ourselves used these datasets in previous research to deal with placement effects&#10;and presented low-level sensor abstractions in motion based on-body sensing.&#10;Researchers, conducting novel data collections, can rely on the toolchain and the the low-level sensor&#10;abstractions summarized in this paper. Additionally, they can draw from our experiences developing and&#10;conducting context recognition experiments.&#10;Our toolchain is already a valuable rapid prototyping tool. Still, we plan to extend it to crowd-based&#10;sensing, enabling the general public to gather context data, learn more about their lives and contribute&#10;to context recognition research.&#10;Applying higher level context reasoning on the gathered context data is a obvious extension to our work.&lt;/p&gt;</description></item></channel></rss>