Thesis full text (PDF) - Politecnico di Milano

classifications, recommendation, transitivity of relations, and static and multi-valued
attributes.
• The available data retrieval mechanisms usually require design-time specification of the
content structure, thus failing to deliver objects when the relations among them are not
known a priori.
These drawbacks become more and more critical in several Web information systems that
require awareness of both system data and its semantics specially in the social network web
applications where reasoning on the user profile as well as other information which could help to
identify common interests among users.
In summary, the application must be integrated with the data semantics and inference mechanism
by which can deduct some interesting information in applications that involve content
personalization, adaptively, recommendation and machine-to-machine sharing. All these
information systems need to make decisions upon knowledge that is derived mainly from their
data and its semantics.
To fulfill such requirements, traditional modeling approaches for Web applications must be
extended from a purely database oriented or object oriented perspective, to a full-fledged
semantics based and ontology based perspective. This involves dramatic changes from static and
syntax-based models to dynamic and semantics-based knowledge.
1.2 Overview of the Approach
To overcome the impuissance of Web applications, new effective and efficient tools are needed
so that application designers move to knowledge-intensive application development, without
losing development productivity and results quality.
We are using a framework [1] for designing and implementing a Web application with
recommendation lineament that leverage data semantics for achieving the abovementioned
results. More precisely, we address three main objectives:
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