Frame detection over the semantic web

In the past, research in ontology learning from text has mainly focused on entity recognition, taxonomy induction and relation extraction. In this work we approach a challenging research issue: detecting semantic frames from texts and using them to encode web ontologies. We exploit a new generation Natural Language Processing technology for frame detection, and we enrich the frames acquired so far with argument restrictions provided by a super-sense tagger and domain specializations. The results are encoded according to a Linguistic MetaModel, which allows a complete translation of lexical resources and data acquired from text, enabling custom transformations of the enriched frames into modular ontology components.

Building a usable and accessible semantic web interaction platform

Semantic Web applications take off is being slower than expected, at least with respect to “real-world” applications and users. One of the main reasons for this lack of adoption is that most Semantic Web user interfaces are still immature from the usability and accessibility points of view. This is due to the novelty of these technologies, but this also motivates the exploration of alternative interaction paradigms, different from the “traditional” Web or Desktop applications ones. Our proposal is realized in the Rhizomer platform, which explores the possibilities of the object–action interaction paradigm at the Web scale. This paradigm is well suited for heterogeneous resource spaces such as those common in the Semantic Web. Resources, described by metadata, correspond to the objects in the paradigm. Semantic web services, which are dynamically associated to these objects, correspond to the actions. The platform is being put into practice in the context of a research project in order to build an open application for media distribution based on Semantic Web technologies. Moreover, its usability and accessibility have been evaluated in this real setting and compared to similar systems.

BioSWR - Semantic Web services Registry for Bioinformatics

Article About the Authors Metrics Comments Related Content Abstract Introduction Functionality Implementation Discussion Acknowledgments Author Contributions References Reader Comments (0) Figures Abstract Despite of the variety of available Web services registries specially aimed at Life Sciences, their scope is usually restricted to a limited set of well-defined types of services. While dedicated registries are generally tied to a particular format, general-purpose ones are more adherent to standards and usually rely on Web Service Definition Language (WSDL). Although WSDL is quite flexible to support common Web services types, its lack of semantic expressiveness led to various initiatives to describe Web services via ontology languages. Nevertheless, WSDL 2.0 descriptions gained a standard representation based on Web Ontology Language (OWL). BioSWR is a novel Web services registry that provides standard Resource Description Framework (RDF) based Web services descriptions along with the traditional WSDL based ones. The registry provides Web-based interface for Web services registration, querying and annotation, and is also accessible programmatically via Representational State Transfer (REST) API or using a SPARQL Protocol and RDF Query Language. BioSWR server is located at http://inb.bsc.es/BioSWR/and its code is available at https://sourceforge.net/projects/bioswr/​under the LGPL license.

eLearning and Semantic Web

Semantic Web: Software agents on the Semantic Web may use commonly agreed service language, which enables co-ordination between agents and proactive delivery of learning materials in the context of actual problems. The vision is that each user has his own personalized agent that communicates with other agents.

Towards semantic web mining

Semantic Web Mining aims at combining the two fast-developing research areas Semantic Web and Web Mining. The idea is to improve, on the one hand, the results of Web Mining by exploiting the new semantic structures in the Web; and to make use of Web Mining, on overview of where the two areas meet today, and sketches ways of how a closer integration could be profitable.

Semantic web mining and the representation, analysis, and evolution of web space

Semantic Web Mining aims at combining the two fast-developing research areas Semantic Web and Web Mining. This survey analyzes the convergence of trends from both areas: Growing numbers of researchers work on improving the results of Web Mining by exploiting semantic structures in the Web, and they use Web Mining techniques for building the Semantic Web. Last but not least, these techniques can be used for mining the Semantic Web itself. The second aim of this paper is to use these concepts to circumscribe what Web space is, what it represents and how it can be represented and analyzed. This is used to sketch the role that Semantic Web Mining and the software agents and human agents involved in it can play in the evolution of Web space.

Context Mediation in the Semantic Web: Handling OWL Ontology and Data Disparity through Context Interchange

The COntext INterchange (COIN) strategy is an approach to solving the problem of interoperability of semantically heterogeneous data sources through context mediation. COIN has used its own notation and syntax for representing ontologies. More recently, the OWL Web Ontology Language is becoming established as the W3C recommended ontology language. We propose the use of the COIN strategy to solve context disparity and ontology interoperability problems in the emerging Semantic Web – both at the ontology level and at the data level. In conjunction with this, we propose a version of the COIN ontology model that uses OWL and the emerging rules interchange language, RuleML.

TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 13: Web Technologies 2 - The Semantic Web

The semantic web represents a current research effort to increase the capability of machines to make sense of content on the web. In this class, Peter Scheir will give a guest lecture on the basic principles underlying the semantic web vision, including RDF, OWL and other standards.

Introduction to the Semantic Web and the Web of Linked Data

Presentation given as part of the EPrints/dotAC training event on 26 Mar 2010.

Semantic Web In Use

Presentation given as part of the EPrints/dotAC training day on 26 Mar 2010.