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Semantically enhanced enforcement of mobile consumer's privacy preferences
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Proceedings of the 2006 ACM symposium on Applied computing table of contents
Dijon, France
SESSION: Mobile computing and applications (MCA) table of contents
Pages: 1172 - 1176  
Year of Publication: 2006
ISBN:1-59593-108-2
Authors
Mahmoud Youssef  Arab Academy for Science & Tech, Alexandria - Egypt
Nabil R. Adam  Rutgers University, University Ave. Newark, NJ
Vijayalakshmi Atluri  Rutgers University, University Ave. Newark, NJ
Sponsor
SIGAPP: ACM Special Interest Group on Applied Computing
Publisher
ACM  New York, NY, USA
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ABSTRACT

In such applications as location-based advertising, merchants use consumers' information to send them personalized advertisements. These applications provide convenience to consumers and competitive advantage to merchants. However, the improper use of consumers' information presents a serious threat to their privacy. It is also important to observe that among the motives for the consumers to accept advertisements is the incentive offered by the merchant. Therefore, such incentive should become a criterion upon which consumers decide to grant or deny access to their information. We propose modeling mobile consumer preferences including incentive-related preferences in an ontology using the Ontology Web Language (OWL) and enforcing these preferences using reasoning techniques. We present modeling of consumer preferences and merchant queries in that ontology and describe how to match them. Moreover, we present a prototype implementation and an evaluation study that shows that query size is more significant than the ontology size.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Mahmoud Youssef: colleagues
Nabil R. Adam: colleagues
Vijayalakshmi Atluri: colleagues