Next Generation Semantic Web Applications

Motta, Enrico; Sabou, Marta

doi:10.1007/11836025_3

Cited by 44 publications

(26 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The broader context of our work is one of providing meaningful mappings that can be used by the next generation of Semantic Web applications [10] to reason over multiple ontologies. Hence, in contrast with most existing work on ontology mapping, we are interested in developing an approach which can be used by systems that need to create mappings dynamically and in real time to make use of the large scale semantics available on the Web.…”

Section: Discussionmentioning

confidence: 99%

Exploring the Semantic Web as Background Knowledge for Ontology Matching

Sabou

d’Aquin

Motta

2008

Journal on Data Semantics XI

Self Cite

111

117

View full text Add to dashboard Cite

Abstract. While current approaches to ontology mapping produce good results by mainly relying on label and structure based similarity measures, there are several cases in which they fail to discover important mappings. In this paper we describe a novel approach to ontology mapping, which is able to avoid this limitation by using background knowledge. Existing approaches relying on background knowledge typically have one or both of two key limitations: 1) they rely on a manually selected reference ontology; 2) they suffer from the noise introduced by the use of semi-structured sources, such as text corpora. Our technique circumvents these limitations by exploiting the increasing amount of semantic resources available online. As a result, there is no need either for a manually selected reference ontology (the relevant ontologies are dynamically selected from an online ontology repository), or for transforming background knowledge in an ontological form. The promising results from experiments on two real life thesauri indicate both that our approach has a high precision and also that it can find mappings, which are typically missed by existing approaches.

show abstract

Section: Discussionmentioning

confidence: 99%

Exploring the Semantic Web as Background Knowledge for Ontology Matching

Sabou

d’Aquin

Motta

2008

Journal on Data Semantics XI

Self Cite

111

117

View full text Add to dashboard Cite

show abstract

“…We have extracted a characterization of semantic applications regarding the characteristics of this type of applications presented in [1,5,6,7]. Figure 1 (1) Use of a single ontology or a network of ontologies (2) Design-time or run-time ontology selection (3) Use of generic or domain-specific ontologies (4) Generation of new ontologies (5) Use of internal or external ontologies (6) Ontologies reuse and reengineering (7) Non-ontological resources reengineering (8) Ontologies dynamicity (9) Centralization or distribution of ontologies (10) Scalabitlity regarding the number of ontologies (11) Scalability regarding the number of ontology elements (12) Ontologies encoding heterogeneity (13) shows the result of the analysis made.…”

Section: Related Workmentioning

confidence: 99%

Guidelines for the Specification and Design of Large-Scale Semantic Applications

Muñoz-García

García‐Castro

2009

The Semantic Web

View full text Add to dashboard Cite

Abstract. This paper presents a set of guidelines to help software engineers with the specification and design of large-scale semantic applications by defining new processes for Requirements Engineering and Design for semantic applications. To facilitate its use to software engineers not experts in semantic technologies, several techniques are provided, namely, a characterization of large-scale semantic applications, common use cases that appear when developing this type of application, and a set of architectural patterns that can be used for modelling the architecture of semantic applications. The paper also presents an example of how these guidelines can be used and an evaluation of our contributions using the W3C Semantic Web use cases.

show abstract

“…Indeed, there is a trend to move away from applications relying on a small amount of manually selected semantic sources towards a new generation of Semantic Web tools which dynamically select, reuse and combine a multitude of heterogeneous, online available ontologies [20,21]. This paradigm of harvesting the Semantic Web has also inspired novel ways of performing a variety of tasks.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Semantic Web: A Task-Based Approach

et al. 2007

Self Cite

View full text Add to dashboard Cite

Abstract. The increased availability of online knowledge has led to the design of several algorithms that solve a variety of tasks by harvesting the Semantic Web, i.e., by dynamically selecting and exploring a multitude of online ontologies. Our hypothesis is that the performance of such novel algorithms implicitly provides an insight into the quality of the used ontologies and thus opens the way to a task-based evaluation of the Semantic Web. We have investigated this hypothesis by studying the lessons learnt about online ontologies when used to solve three tasks: ontology matching, folksonomy enrichment, and word sense disambiguation. Our analysis leads to a suit of conclusions about the status of the Semantic Web, which highlight a number of strengths and weaknesses of the semantic information available online and complement the findings of other analysis of the Semantic Web landscape.

show abstract

Next Generation Semantic Web Applications

Cited by 44 publications

References 13 publications

Exploring the Semantic Web as Background Knowledge for Ontology Matching

Exploring the Semantic Web as Background Knowledge for Ontology Matching

Guidelines for the Specification and Design of Large-Scale Semantic Applications

Evaluating the Semantic Web: A Task-Based Approach

Contact Info

Product

Resources

About