<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-14T20:00:10Z</responseDate><request verb="GetRecord" identifier="oai:gredos.usal.es:10366/143306" metadataPrefix="mods">https://gredos.usal.es/oai/request</request><GetRecord><record><header><identifier>oai:gredos.usal.es:10366/143306</identifier><datestamp>2025-06-05T12:36:20Z</datestamp><setSpec>com_10366_142734</setSpec><setSpec>com_10366_122682</setSpec><setSpec>com_10366_4666</setSpec><setSpec>com_10366_3823</setSpec><setSpec>col_10366_143142</setSpec></header><metadata><mods:mods xmlns:mods="http://www.loc.gov/mods/v3" xmlns:doc="http://www.lyncode.com/xoai" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd">
<mods:name>
<mods:namePart>Hussain, Naveed</mods:namePart>
</mods:name>
<mods:name>
<mods:namePart>Mirza, Hamid Turab</mods:namePart>
</mods:name>
<mods:name>
<mods:namePart>Hussain, Ibrar</mods:namePart>
</mods:name>
<mods:extension>
<mods:dateAvailable encoding="iso8601">2020-06-23T11:12:08Z</mods:dateAvailable>
</mods:extension>
<mods:extension>
<mods:dateAccessioned encoding="iso8601">2020-06-23T11:12:08Z</mods:dateAccessioned>
</mods:extension>
<mods:originInfo>
<mods:dateIssued encoding="iso8601">2019-03-14</mods:dateIssued>
</mods:originInfo>
<mods:identifier type="citation">ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 8 (2019)</mods:identifier>
<mods:identifier type="issn">2255-2863</mods:identifier>
<mods:identifier type="uri">http://hdl.handle.net/10366/143306</mods:identifier>
<mods:abstract>Online reviews about the purchase of a product or services provided have become the main source of user opinions. To gain profit or fame usually spam reviews are written to promote or demote some target products or services. This practice is known as review spamming. In the last few years, different methods have been suggested to solve the problem of review spamming but there is still a need to introduce new spam review detection method to improve accuracy results. In this work, researchers have studied six different spammer behavioral features and analyzed the proposed spam review detection method using weight method. An experimental evaluation was conducted on a benchmark dataset and achieved 84.5% accuracy.</mods:abstract>
<mods:language>
<mods:languageTerm>eng</mods:languageTerm>
</mods:language>
<mods:accessCondition type="useAndReproduction">info:eu-repo/semantics/openAccess</mods:accessCondition>
<mods:accessCondition type="useAndReproduction">info:eu-repo/semantics/openAccess</mods:accessCondition>
<mods:subject>
<mods:topic>Computación</mods:topic>
</mods:subject>
<mods:subject>
<mods:topic>Informótica</mods:topic>
</mods:subject>
<mods:subject>
<mods:topic>Computing</mods:topic>
</mods:subject>
<mods:subject>
<mods:topic>Information Technology</mods:topic>
</mods:subject>
<mods:titleInfo>
<mods:title>Detecting Spam Review through Spammer’s Behavior Analysis</mods:title>
</mods:titleInfo>
<mods:genre>info:eu-repo/semantics/article</mods:genre>
</mods:mods></metadata></record></GetRecord></OAI-PMH>