Semantically enhanced enforcement of mobile consumer's privacy preferences

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.