<?xml version="1.0" encoding="UTF-8"?>
<XML><RECORDS>
<RECORD>
	<REFERENCE_TYPE>0</REFERENCE_TYPE>
	<AUTHORS>
		<AUTHOR>Doherty, Aiden R.</AUTHOR>
		<AUTHOR>Smeaton, Alan F.</AUTHOR>
	</AUTHORS>
	<YEAR>2010</YEAR>
	<TITLE>Automatically augmenting lifelog events using pervasively generated content from millions of people</TITLE>
	<SECONDARY_TITLE>In: Sensors</SECONDARY_TITLE>
	<PUBLISHER>Molecular Diversity Preservation International (MDPI)</PUBLISHER>
	<VOLUME>10</VOLUME>
	<NUMBER>3</NUMBER>
	<PAGES>1423-1446</PAGES>
	<DATE>February 2010</DATE>
	<KEYWORDS>
		<KEYWORD>RP5</KEYWORD>
	</KEYWORDS>
	<ABSTRACT>&lt;p&gt;In sensor research we take advantage of additional contextual sensor  information to disambiguate potentially erroneous sensor readings or to  make better informed decisions on a single sensor's output. This use of  additional information reinforces, validates, semantically enriches, and  augments sensed data. Lifelog data is challenging to augment, as it  tracks one's life with many images including the places they go, making  it non-trivial to find associated sources of information. We investigate  realising the goal of pervasive user-generated content based on  sensors, by augmenting passive visual lifelogs with &amp;quot;Web 2.0&amp;quot; content  collected by millions of other individuals.&lt;/p&gt;</ABSTRACT>
	<URL>http://doras.dcu.ie/15300/</URL>
</RECORD>
</RECORDS></XML>