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Article: Complex problem solving: Identity matching based on social contextual information

TitleComplex problem solving: Identity matching based on social contextual information
Authors
KeywordsComplex problems
Design science
Identity matching
Social contextual information
Issue Date2007
PublisherAssociation for Information Systems. The Journal's web site is located at http://jais.aisnet.org/
Citation
Journal Of The Association Of Information Systems, 2007, v. 8 n. 10, p. article no. 2, 525-545 How to Cite?
AbstractComplex problems like drug crimes often involve a large number of variables interacting with each other. A complex problem may be solved by breaking it into parts (i.e., sub-problems), which can be tackled more easily. The identity matching problem, for example, is a part of the problem of drug and other types of crimes. It is often encountered during crime investigations when a single criminal is represented by multiple identity records in law enforcement databases. Because of the discrepancies among these records, a single criminal may appear to be different people. Following Enid Mumford's three-stage problem solving framework, we design a new method to address the problem of criminal identity matching for fighting drug-related crimes. Traditionally, the complexity of criminal identity matching was reduced by treating criminals as isolated individuals who maintain certain personal identities. In this research, we recognize the intrinsic complexity of the problem and treat criminals as interrelated rather than isolated individuals. In other words, we take into consideration of the social relationships between criminals during the matching process. We study not only the personal identities but also the social identities of criminals. Evaluation results were quite encouraging and showed that combining social features with personal features could improve the performance of criminal identity matching. In particular, the social features become more useful when data contain many missing values for personal attributes. Copyright © 2007, by the Association for Information Systems.
Persistent Identifierhttp://hdl.handle.net/10722/85913
ISSN
2015 Impact Factor: 1.79
2015 SCImago Journal Rankings: 1.786
References

 

DC FieldValueLanguage
dc.contributor.authorXu, Jen_HK
dc.contributor.authorWang, GAen_HK
dc.contributor.authorLi, Jen_HK
dc.contributor.authorChau, Men_HK
dc.date.accessioned2010-09-06T09:10:41Z-
dc.date.available2010-09-06T09:10:41Z-
dc.date.issued2007en_HK
dc.identifier.citationJournal Of The Association Of Information Systems, 2007, v. 8 n. 10, p. article no. 2, 525-545en_HK
dc.identifier.issn1536-9323en_HK
dc.identifier.urihttp://hdl.handle.net/10722/85913-
dc.description.abstractComplex problems like drug crimes often involve a large number of variables interacting with each other. A complex problem may be solved by breaking it into parts (i.e., sub-problems), which can be tackled more easily. The identity matching problem, for example, is a part of the problem of drug and other types of crimes. It is often encountered during crime investigations when a single criminal is represented by multiple identity records in law enforcement databases. Because of the discrepancies among these records, a single criminal may appear to be different people. Following Enid Mumford's three-stage problem solving framework, we design a new method to address the problem of criminal identity matching for fighting drug-related crimes. Traditionally, the complexity of criminal identity matching was reduced by treating criminals as isolated individuals who maintain certain personal identities. In this research, we recognize the intrinsic complexity of the problem and treat criminals as interrelated rather than isolated individuals. In other words, we take into consideration of the social relationships between criminals during the matching process. We study not only the personal identities but also the social identities of criminals. Evaluation results were quite encouraging and showed that combining social features with personal features could improve the performance of criminal identity matching. In particular, the social features become more useful when data contain many missing values for personal attributes. Copyright © 2007, by the Association for Information Systems.en_HK
dc.languageengen_HK
dc.publisherAssociation for Information Systems. The Journal's web site is located at http://jais.aisnet.org/en_HK
dc.relation.ispartofJournal of the Association of Information Systemsen_HK
dc.subjectComplex problemsen_HK
dc.subjectDesign scienceen_HK
dc.subjectIdentity matchingen_HK
dc.subjectSocial contextual informationen_HK
dc.titleComplex problem solving: Identity matching based on social contextual informationen_HK
dc.typeArticleen_HK
dc.identifier.emailChau, M: mchau@hkucc.hku.hken_HK
dc.identifier.authorityChau, M=rp01051en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-58149472196en_HK
dc.identifier.hkuros148562en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-58149472196&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume8en_HK
dc.identifier.issue10en_HK
dc.identifier.spagearticle no. 2, 525en_HK
dc.identifier.epage545en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridXu, J=36006847900en_HK
dc.identifier.scopusauthoridWang, GA=7407148134en_HK
dc.identifier.scopusauthoridLi, J=35205817400en_HK
dc.identifier.scopusauthoridChau, M=7006073763en_HK

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