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  <event:Event rdf:about="http://ebiquity.umbc.edu/event/html/id/169/Personalized-Information-Retrieval-in-Context">
    <rdfs:label><![CDATA[Personalized Information Retrieval in Context]]></rdfs:label>
    <event:title><![CDATA[Personalized Information Retrieval in Context]]></event:title>
    <event:speaker><person:Visitor rdf:about="http://ebiquity.umbc.edu/person/html/David/Vallet/"><person:name><![CDATA[David  Vallet]]></person:name><rdfs:label><![CDATA[David  Vallet]]></rdfs:label></person:Visitor></event:speaker>
    <event:startDate rdf:datatype="&xsd;dateTime">2006-09-05T11:15:00-05:00</event:startDate>
    <event:endDate rdf:datatype="&xsd;dateTime">2006-09-05T10:50:00-05:00</event:endDate>
    <event:location><![CDATA[ITE 325b]]></event:location>
    <event:abstract><![CDATA[Personalized content retrieval aims at improving the retrieval
process by taking into account the particular interests
of individual users. However, not all user preferences are
relevant in all situations. It is well known that human preferences
are complex, multiple, heterogeneous, changing,
even contradictory, and should be understood in context
with the user goals and tasks at hand. We propose
a method to build a dynamic representation of the semantic
context of ongoing retrieval tasks, which is used to
activate different subsets of user interests at runtime, in such
a way that out of context preferences are discarded. Our approach
is based on an ontology-driven representation of the
domain of discourse, providing enriched descriptions of the
semantics involved in retrieval actions and preferences, and
enabling the definition of effective means to relate preferences
and context.]]></event:abstract>
    <event:tag><![CDATA[information retrieval]]></event:tag>
    <event:tag><![CDATA[context]]></event:tag>
    <assert:eventPptSlides rdf:resource="http://ebiquity.umbc.edu/resource/html/id/199/Personalized-Information-Retrieval-in-Context" />
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