1,806 research outputs found
Discovering the Impact of Knowledge in Recommender Systems: A Comparative Study
Recommender systems engage user profiles and appropriate filtering techniques
to assist users in finding more relevant information over the large volume of
information. User profiles play an important role in the success of
recommendation process since they model and represent the actual user needs.
However, a comprehensive literature review of recommender systems has
demonstrated no concrete study on the role and impact of knowledge in user
profiling and filtering approache. In this paper, we review the most prominent
recommender systems in the literature and examine the impression of knowledge
extracted from different sources. We then come up with this finding that
semantic information from the user context has substantial impact on the
performance of knowledge based recommender systems. Finally, some new clues for
improvement the knowledge-based profiles have been proposed.Comment: 14 pages, 3 tables; International Journal of Computer Science &
Engineering Survey (IJCSES) Vol.2, No.3, August 201
SKOS and the Semantic Web: Knowledge Organization, Metadata, and Interoperability
The Simplified Knowledge Organization System (SKOS) is a Semantic Web framework, based on the Resource Description Framework (RDF) for thesauri, classification schemes and simple ontologies. It allows for machine-actionable description of the structure of these knowledge organization systems (KOS) and provides an excellent tool for addressing interoperability and vocabulary control problems inherent to the rapidly expanding information environment of the Web. This paper discusses the foundations of the SKOS framework and reviews the literature on a variety of SKOS implementations. The limitations of SKOS that have been revealed through its broad application are addressed with brief attention to the proposed extensions to the framework intended to account for them
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Grid-based semantic integration of heterogeneous data resources: Implementation on a HealthGrid
This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel University.The semantic integration of geographically distributed and heterogeneous data
resources still remains a key challenge in Grid infrastructures. Today's
mainstream Grid technologies hold the promise to meet this challenge in a
systematic manner, making data applications more scalable and manageable. The
thesis conducts a thorough investigation of the problem, the state of the art, and
the related technologies, and proposes an Architecture for Semantic Integration of
Data Sources (ASIDS) addressing the semantic heterogeneity issue. It defines a
simple mechanism for the interoperability of heterogeneous data sources in order
to extract or discover information regardless of their different semantics. The
constituent technologies of this architecture include Globus Toolkit (GT4) and
OGSA-DAI (Open Grid Service Architecture Data Integration and Access)
alongside other web services technologies such as XML (Extensive Markup
Language). To show this, the ASIDS architecture was implemented and tested in a
realistic setting by building an exemplar application prototype on a HealthGrid
(pilot implementation).
The study followed an empirical research methodology and was informed by
extensive literature surveys and a critical analysis of the relevant technologies and
their synergies. The two literature reviews, together with the analysis of the
technology background, have provided a good overview of the current Grid and
HealthGrid landscape, produced some valuable taxonomies, explored new paths
by integrating technologies, and more importantly illuminated the problem and
guided the research process towards a promising solution. Yet the primary
contribution of this research is an approach that uses contemporary Grid
technologies for integrating heterogeneous data resources that have semantically
different. data fields (attributes). It has been practically demonstrated (using a
prototype HealthGrid) that discovery in semantically integrated distributed data
sources can be feasible by using mainstream Grid technologies, which have been
shown to have some Significant advantages over non-Grid based approaches
A Preliminary SKOS Implementation of the Art and Architecture Thesaurus: Machine-Actionable Controlled Vocabulary for the Semantic Web
This paper presents an experimental implementation of the Art and Architecture Thesaurus, a knowledge organizational system for the visual arts and architecture, within the SKOS (Simple Knowledge Organization System) framework. Such treatment allows for machine-actionability on thesaurus records for automated expansion of search queries and also provides a framework for interoperability across metadata schemas in a linked data environment. SKOS enables more complex semantic processing by utilizing a simple framework for Semantic Web technology within thesauri. The analysis establishes an application profile for AAT, which accommodates the faceted and polyhierarchical structure of the thesaurus, as well as the detailed source referencing contained within AAT’s documentary note
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