10,703 research outputs found
Realization of Semantic Atom Blog
Web blog is used as a collaborative platform to publish and share
information. The information accumulated in the blog intrinsically contains the
knowledge. The knowledge shared by the community of people has intangible value
proposition. The blog is viewed as a multimedia information resource available
on the Internet. In a blog, information in the form of text, image, audio and
video builds up exponentially. The multimedia information contained in an Atom
blog does not have the capability, which is required by the software processes
so that Atom blog content can be accessed, processed and reused over the
Internet. This shortcoming is addressed by exploring OWL knowledge modeling,
semantic annotation and semantic categorization techniques in an Atom blog
sphere. By adopting these techniques, futuristic Atom blogs can be created and
deployed over the Internet
Interpr\'etation vague des contraintes structurelles pour la RI dans des corpus de documents XML - \'Evaluation d'une m\'ethode approch\'ee de RI structur\'ee
We propose specific data structures designed to the indexing and retrieval of
information elements in heterogeneous XML data bases. The indexing scheme is
well suited to the management of various contextual searches, expressed either
at a structural level or at an information content level. The approximate
search mechanisms are based on a modified Levenshtein editing distance and
information fusion heuristics. The implementation described highlights the
mixing of structured information presented as field/value instances and free
text elements. The retrieval performances of the proposed approach are
evaluated within the INEX 2005 evaluation campaign. The evaluation results rank
the proposed approach among the best evaluated XML IR systems for the VVCAS
task.Comment: 26 pages, ISBN 978-2-7462-1969-
A random forest system combination approach for error detection in digital dictionaries
When digitizing a print bilingual dictionary, whether via optical character
recognition or manual entry, it is inevitable that errors are introduced into
the electronic version that is created. We investigate automating the process
of detecting errors in an XML representation of a digitized print dictionary
using a hybrid approach that combines rule-based, feature-based, and language
model-based methods. We investigate combining methods and show that using
random forests is a promising approach. We find that in isolation, unsupervised
methods rival the performance of supervised methods. Random forests typically
require training data so we investigate how we can apply random forests to
combine individual base methods that are themselves unsupervised without
requiring large amounts of training data. Experiments reveal empirically that a
relatively small amount of data is sufficient and can potentially be further
reduced through specific selection criteria.Comment: 9 pages, 7 figures, 10 tables; appeared in Proceedings of the
Workshop on Innovative Hybrid Approaches to the Processing of Textual Data,
April 201
Web Service Discovery in a Semantically Extended UDDI Registry: the Case of FUSION
Service-oriented computing is being adopted at an unprecedented rate, making the effectiveness of automated service discovery an increasingly important challenge. UDDI has emerged as a de facto industry standard and fundamental building block within SOA infrastructures. Nevertheless, conventional UDDI registries lack means to provide unambiguous, semantically rich representations of Web service capabilities, and the logic inference power required for facilitating automated service discovery. To overcome this important limitation, a number of approaches have been proposed towards augmenting Web service discovery with semantics. This paper discusses the benefits of semantically extending Web service descriptions and UDDI registries, and presents an overview of the approach put forward in project FUSION, towards semantically-enhanced publication and discovery of services based on SAWSDL
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