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		<title>A. et al 2020a - Revision history</title>
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		<updated>2026-04-11T05:54:59Z</updated>
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		<id>https://www.scipedia.com/wd/index.php?title=A._et_al_2020a&amp;diff=202408&amp;oldid=prev</id>
		<title>Scipediacontent: Scipediacontent moved page Draft Content 291157536 to A. et al 2020a</title>
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				<updated>2021-02-02T05:49:03Z</updated>
		
		<summary type="html">&lt;p&gt;Scipediacontent moved page &lt;a href=&quot;/public/Draft_Content_291157536&quot; class=&quot;mw-redirect&quot; title=&quot;Draft Content 291157536&quot;&gt;Draft Content 291157536&lt;/a&gt; to &lt;a href=&quot;/public/A._et_al_2020a&quot; title=&quot;A. et al 2020a&quot;&gt;A. et al 2020a&lt;/a&gt;&lt;/p&gt;
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				&lt;td colspan='1' style=&quot;background-color: white; color:black; text-align: center;&quot;&gt;← Older revision&lt;/td&gt;
				&lt;td colspan='1' style=&quot;background-color: white; color:black; text-align: center;&quot;&gt;Revision as of 05:49, 2 February 2021&lt;/td&gt;
				&lt;/tr&gt;&lt;tr&gt;&lt;td colspan='2' style='text-align: center;' lang='en'&gt;&lt;div class=&quot;mw-diff-empty&quot;&gt;(No difference)&lt;/div&gt;
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		<author><name>Scipediacontent</name></author>	</entry>

	<entry>
		<id>https://www.scipedia.com/wd/index.php?title=A._et_al_2020a&amp;diff=202407&amp;oldid=prev</id>
		<title>Scipediacontent: Created page with &quot; == Abstract ==  Identifying the portions of trajectory data where movement ends and a significant stop starts is a basic, yet fundamental task that can affect the quality of...&quot;</title>
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				<updated>2021-02-02T05:48:57Z</updated>
		
		<summary type="html">&lt;p&gt;Created page with &amp;quot; == Abstract ==  Identifying the portions of trajectory data where movement ends and a significant stop starts is a basic, yet fundamental task that can affect the quality of...&amp;quot;&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;&lt;br /&gt;
== Abstract ==&lt;br /&gt;
&lt;br /&gt;
Identifying the portions of trajectory data where movement ends and a significant stop starts is a basic, yet fundamental task that can affect the quality of any mobility analytics process. Most of the many existing solutions adopted by researchers and practitioners are simply based on fixed spatial and temporal thresholds stating when the moving object remained still for a significant amount of time, yet such thresholds remain as static parameters for the user to guess. In this work we study the trajectory segmentation from a multi-granularity perspective, looking for a better understanding of the problem and for an automatic, parameter-free and user-adaptive solution that flexibly adjusts the segmentation criteria to the specific user under study. Experiments over real data and comparison against simple competitors show that the flexibility of the proposed method has a positive impact on results.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Original document ==&lt;br /&gt;
&lt;br /&gt;
The different versions of the original document can be found in:&lt;br /&gt;
&lt;br /&gt;
* [https://publications.cnr.it/doc/424845 https://publications.cnr.it/doc/424845]&lt;/div&gt;</summary>
		<author><name>Scipediacontent</name></author>	</entry>

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