Architecture for Including Personalization in a Mobile GIS via Semantic Web Techniques - Geographical Information Systems: Trends and Technologies - page 212

have access to structured collection of information and sets of inference rules
that can be used to conduct automated reasoning (Berners-lee et al. 2001).
To achieve these requirements, Semantic Web languages and ontologies
have been developed for knowledge representation, and Semantic Web
reasoners have been introduced for inferring knowledge.
Ontologies are the cornerstone of the Semantic Web and are used
for organizing data, improving a search or data integration. They can be
defi ned as conceptual models of reality written in a language interpreted
by a program, which represent concepts and relationships of a specifi c
domain. They can acquire or share knowledge about a system and use
this knowledge for a specifi c purpose, such as designing or developing
software, designing a database or understanding how a specifi c system
works (Guarino 1998).
On the other hand, Semantic Web allows inferring new information
creating new relations between data. This is done using Semantic Web
reasoners, which are programs that infer logical consequences from a set
of explicitly asserted facts or axioms, and typically provides automated
support for reasoning tasks such as classifi cation, debugging and querying
(Dentler et al. 2011).
Through reasoners it is possible to infer new information from
ontologies (Bry and Marchiori 2005). The inference rules are commonly
specifi ed by means of an ontology language, and often a description
language. For instance, using an ontology that describes simple preferences
of a user allows inferring more sophisticated preferences. Schickel-Zuber
and Faltings (2006) presented examples of the benefi ts of ontologies in
recommender systems. Bradley et al. (2000) used an ontology to build a
personalized search engine that increased classifi cation accuracy by more
than 60% and Middleton et al . (2004) used ontological relationships between
topics of interest to infer other topics of interest, which might not have been
browsed explicitly.
Therefore, using ontologies and reasoners in the appropriate context,
it is possible to develop a system able of reasoning, in a minor extent, as
a person, what we can call an intelligent system. This could be especially
useful to fi lter the big quantity of data available on the Web taking into
account user interests and geographic location.
Current Ontologies
To implement technologies of the Semantic Web in a location-aware system
for tourism application, it is necessary to defi ne the ontologies of every
domain involved in the project and consider some rules for personalization
of data, defi ning forms of reasoning that might be needed to provide the
required data (Bry and Marchiori 2005).