<mets:mets OBJID="oai:generic.eprints.org:215" LABEL="Eprints Item" xsi:schemaLocation="http://www.loc.gov/METS/ http://www.loc.gov/standards/mets/mets.xsd http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-0.xsd" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:mods="http://www.loc.gov/mods/v3" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mets="http://www.loc.gov/METS/"><mets:metsHdr CREATEDATA="2019-02-15T09:06:46Z"><mets:agent TYPE="ORGANIZATION" ROLE="CUSTODIAN"><mets:name>WWW2009 EPrints</mets:name></mets:agent></mets:metsHdr><mets:dmdSec ID="DMD_oai:generic.eprints.org:215_mods"><mets:mdWrap MDTYPE="mods"><mets:xmlData><mods:titleInfo><mods:title>Mining the Web 2.0 for Better Search</mods:title></mods:titleInfo><mods:name type="personal"><mods:namePart type="given"> Ricardo</mods:namePart><mods:namePart type="family">Baeza-Yates</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:abstract>There are several semantic sources that can be found in the Web that are either explicit, e.g. Wikipedia, or implicit, e.g. derived from Web usage data. Most of them are related to user generated content (UGC) or what is called today the Web 2.0. In this talk we show several applications of mining the wisdom of crowds behind UGC to improve search. We will show live demos to find relations in the Wikipedia or to improve image search as well as our current research in the topic. Our final goal is to produce a virtuous data feedback circuit to leverage the Web itself.</mods:abstract><mods:originInfo><mods:dateIssued encoding="iso8061">2009-04</mods:dateIssued></mods:originInfo><mods:genre>Conference or Workshop Item</mods:genre></mets:xmlData></mets:mdWrap></mets:dmdSec><mets:amdSec ID="TMD_oai:generic.eprints.org:215"><mets:rightsMD ID="rights_oai:generic.eprints.org:215_mods"><mets:mdWrap MDTYPE="mods"><mets:xmlData><mods:useAndReproduction>
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