SEKE 2012 Proceedings - Knowledge Systems Institute

A Context Ontology Model for Pervasive Advertising: a Case Study on Pervasive
Displays
Frederico Moreira Bublitz 1 , Hyggo Oliveira de Almeida 2 , and Angelo Perkusich 2
fredbublitz@uepb.edu.br, hyggo@dsc.ufcg.edu.br, perkusic@dee.ufcg.edu.br
1 State University of Paraiba, 2 Federal University of Campina Grande
Campina Grande, Brazil
Abstract
Context awareness is a key concept for Pervasive Advertising.
However, the literature indicates that there is a lack
of high level abstraction models that enable applications
establish a common vocabulary to share contextual information.
In this paper we present an ontology model for pervasive
advertising. The main aspects of this model is that
it is comprehensive and extensible. Its feasibility is demonstrated
in a case study on a pervasive display scenario.
1. Introduction
As a new channel for communication, Pervasive Computing
[1] offers the opportunity of delivering advertisements
at anytime and anywhere. Once these advertisements
can be delivered through personal devices, this paradigm
enables to achieve a level of audience that was never imagined
before. More than a new channel for delivering advertisements,
the most important aspect of Pervasive Advertising
is that it enables the delivering of contextualized
advertisements [2].
An advertisement is contextualized if it is delivered in
accordance with the context of the user to became more appropriated
and adapted to the situation. In pervasive computing
paradigm, context is defined as any information that
applications can use to provide relevant services or information
to an entity [3]. In case of advertising applications,
the context is defined as any information used to determine
the relevance of an advertisement for a user. For example,
how an application knows if an advertisement of a happy
hour promotion is relevant to you? To answer this question
the application must know about your preferences, location,
activity, friends, and so on.
The contextual information can be obtained from distinct
and heterogeneous sources. This includes the information
that the user can explicitly provides, and the information
that can be obtained from a device, either by sensors or inferred
from other information. In this way, it is necessary
to provide an unified and high level abstraction model to
enable applications to “understand” the meaning of the collected
information and also to establish a common vocabulary
to share this information [4].
As can be noticed, to be aware of the context is important
for effective delivery of contextualized advertisements.
However the literature indicates that there is a lack of high
level abstraction contextual models for Pervasive Advertising.
The reason for this absence of effective solutions occurs
because it is almost impossible to define a priori what
kind information should be used to represent the context,
once it is closely related the product to be announced. For
example, the body temperature of a person may be a relevant
information in order to deliver an advertisement in
health care domain, but it can be unnecessary for determine
the relevance of an announcement of a car.
Notice that this problem is equivalent to the problem of
create a model to represent context in Pervasive Computing.
Several works ware developed over this problem, but
a deeper analysis reveals that this is still an opened problem.
The existent approaches can be comprehensive, but it
is possible to notice that the kind of information modeled in
these works is strongly coupled to some domain of application.
Other works uses a synthetic set of information that
can be used in most domains of applications, but this is not
efficient in practice [5], see more details in Section 2.
In view of the above, in this paper we present a high level
abstraction model for context in Pervasive Advertising, described
in Section 3. The main features of this model are:
(i) it is comprehensive; and (ii) it is loose coupled. That is, it
contemplates many domains of information associated with
the products and can be easily extended to contemplate new
concepts.
The feasibility of the model is demonstrated through a
case study on a pervasive display scenario, detailed in Section
4. In this scenario, the content of a public display is
selected according to the context of the group of consumers
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