Design and evaluation of a multi-agent collaborative Web mining system

Persistent Link:
http://hdl.handle.net/10150/105861
Title:
Design and evaluation of a multi-agent collaborative Web mining system
Author:
Chau, Michael; Zeng, Daniel; Chen, Hsinchun; Huang, Michael; Hendriawan, David
Citation:
Design and evaluation of a multi-agent collaborative Web mining system 2003-04, 35(1):167-183 Decision Support Systems
Publisher:
Elsevier
Journal:
Decision Support Systems
Issue Date:
Apr-2003
Description:
Artificial Intelligence Lab, Department of MIS, University of Arizona
URI:
http://hdl.handle.net/10150/105861
Submitted date:
2004-08-16
Abstract:
Most existing Web search tools work only with individual users and do not help a user benefit from previous search experiences of others. In this paper, we present the Collaborative Spider, a multi-agent system designed to provide post-retrieval analysis and enable across-user collaboration in Web search and mining. This system allows the user to annotate search sessions and share them with other users. We also report a user study designed to evaluate the effectiveness of this system. Our experimental findings show that subjectsâ search performance was degraded, compared to individual search scenarios in which users had no access to previous searches, when they had access to a limited number (e.g., 1 or 2) of earlier search sessions done by other users. However, search performance improved significantly when subjects had access to more search sessions. This indicates that gain from collaboration through collaborative Web searching and analysis does not outweigh the overhead of browsing and comprehending other usersâ past searches until a certain number of shared sessions have been reached. In this paper, we also catalog and analyze several different types of user collaboration behavior observed in the context of Web mining.
Type:
Journal Article (Paginated)
Language:
en
Keywords:
Web Mining; Internet
Local subject classification:
National Science Digital Library; NSDL; Artificial Intelligence lab; AI lab; Web searching; Web content mining; Collaborative information retrieval; Collaboration behavior; Collaborative filtering; Multiagent; Systems; Software agents; Post-retrieval analysis

Full metadata record

DC FieldValue Language
dc.contributor.authorChau, Michaelen_US
dc.contributor.authorZeng, Danielen_US
dc.contributor.authorChen, Hsinchunen_US
dc.contributor.authorHuang, Michaelen_US
dc.contributor.authorHendriawan, Daviden_US
dc.date.accessioned2004-08-16T00:00:01Z-
dc.date.available2010-06-18T23:35:43Z-
dc.date.issued2003-04en_US
dc.date.submitted2004-08-16en_US
dc.identifier.citationDesign and evaluation of a multi-agent collaborative Web mining system 2003-04, 35(1):167-183 Decision Support Systemsen_US
dc.identifier.urihttp://hdl.handle.net/10150/105861-
dc.descriptionArtificial Intelligence Lab, Department of MIS, University of Arizonaen_US
dc.description.abstractMost existing Web search tools work only with individual users and do not help a user benefit from previous search experiences of others. In this paper, we present the Collaborative Spider, a multi-agent system designed to provide post-retrieval analysis and enable across-user collaboration in Web search and mining. This system allows the user to annotate search sessions and share them with other users. We also report a user study designed to evaluate the effectiveness of this system. Our experimental findings show that subjectsâ search performance was degraded, compared to individual search scenarios in which users had no access to previous searches, when they had access to a limited number (e.g., 1 or 2) of earlier search sessions done by other users. However, search performance improved significantly when subjects had access to more search sessions. This indicates that gain from collaboration through collaborative Web searching and analysis does not outweigh the overhead of browsing and comprehending other usersâ past searches until a certain number of shared sessions have been reached. In this paper, we also catalog and analyze several different types of user collaboration behavior observed in the context of Web mining.en_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectWeb Miningen_US
dc.subjectInterneten_US
dc.subject.otherNational Science Digital Libraryen_US
dc.subject.otherNSDLen_US
dc.subject.otherArtificial Intelligence laben_US
dc.subject.otherAI laben_US
dc.subject.otherWeb searchingen_US
dc.subject.otherWeb content miningen_US
dc.subject.otherCollaborative information retrievalen_US
dc.subject.otherCollaboration behavioren_US
dc.subject.otherCollaborative filteringen_US
dc.subject.otherMultiagenten_US
dc.subject.otherSystemsen_US
dc.subject.otherSoftware agentsen_US
dc.subject.otherPost-retrieval analysisen_US
dc.titleDesign and evaluation of a multi-agent collaborative Web mining systemen_US
dc.typeJournal Article (Paginated)en_US
dc.identifier.journalDecision Support Systemsen_US
All Items in UA Campus Repository are protected by copyright, with all rights reserved, unless otherwise indicated.