Catálogo de publicaciones - libros

A true semantic web of data requires dynamic, real-time interopera-bility between disparate data sources, developed by different organizations in different ways, each for their own specific purposes. Ontology languages provide a means to relate data items to each other in logically well-defined ways, producing complex logical structures with an underlying formal semantics. Whilst these structures have a logical formal semantics, they lack a pragmatic semantics linking them in a systematic and unambiguous way to the real world entities they represent. Thus they are intricate "castles in the air", which may certainly have pathways built to link them together, but lack the solid foundations required for robust real-time dynamic interoperability between structures not mapped to each other in the design stage. Current ontology interoperability strategies lack such a meaning-based arbitrator, and depend instead on human mediation or heuristic approaches. This paper introduces the symbol grounding problem, explains its relevance for the Semantic Web, illustrates how inappropriate correspondence between symbol and referent can result in logically valid but meaningless inferences, examines some of the shortcomings of the current approach in dealing effectively at the level of meaning, and concludes with some ideas for identifying effective grounding strategies.

The measurement of the semantic relatedness has many applications in natural language processing, and many different measures have been proposed. Most of these measures use WordNet as their central resource and not domain ontologies of a particular context. We propose and evaluate a semantic relatedness measure for OWL domain ontologies that concludes to the semantic ranking of ontological, grammatically-related structures. This procedure is used to disambiguate in a particular domain of context and represent in an ontology query language, natural language expressions. The ontology query language that we use is the SPARQL. The construction of the queries is automated and also dependent on the semantic relatedness measurement of ontology concepts. The methodology has been successfully integrated into the OntoNL Framework, a natural language interface generator for knowledge repositories. The experimentations show a good performance in a number of OWL ontologies.

We propose to manually annotate web pages with computer-processable con trolled natural language. These annotations have well-defined formal properties and can be used as query relevant summaries to automatically answer questions expressed in controlled natural language, and as the basis for other forms of automated reasoning. Last, but not least, the annotations can also serve as human-readable summaries of the contents of the web pages. Arguably, annotations written in controlled natural language can bridge the gap between informal and formal notations and leverage true collaboration between humans and machines. This is a position paper that proposes a solution combining existing methods and techniques to achieve a highly relevant practical goal, namely how to effectively access information on the web. However, our solution introduces a "chicken and egg" problem: a critical mass of web annotations will be necessary that people perceive the value of these annotations and start annotating web pages themselves. Only the future will show whether this – basically non-technical – problem can be solved.

Providing a natural language interface to ontologies will not only offer ordinary users the convenience of acquiring needed information from ontologies, but also expand the influence of ontologies and the semantic web consequently. This paper presents PANTO, a Portable nAtural laNguage inTerface to Ontologies, which accepts generic natural language queries and outputs SPARQL queries. Based on a special consideration on nominal phrases, it adopts a triple-based data model to interpret the parse trees output by an off-the-shelf parser. Complex modifications in natural language queries such as negations, superlative and comparative are investigated. The experiments have shown that PANTO provides state-of-the-art results.

ining non-taxonomic relations is an important part of the Semantic Web puzzle. Building on the work of the semantic annotation community, we address the problem of extracting relation instances among annotated entities. In particular, we analyze the problem of verb-based relation instantiation in some detail and present a heuristic domain independent approach, based on verb chunking and entity clustering, which doesn’t require parsing. We also address the problem of mapping linguistic tuples to relations from the ontology. A case study conducted within the biography domain demonstrates the validity of our results in contrast to related work, whilst examining the complexity of the extraction task and the feasibility of verb-based extraction in general.

Wikis are established means for the collaborative authoring, versioning and publishing of textual articles. The Wikipedia project, for example, succeeded in creating the by far largest encyclopedia just on the basis of a wiki. Recently, several approaches have been proposed on how to extend wikis to allow the creation of structured and semantically enriched content. However, the means for creating semantically enriched structured content are already available and are, although unconsciously, even used by Wikipedia authors. In this article, we present a method for revealing this structured content by extracting information from template instances. We suggest ways to efficiently query the vast amount of extracted information (e.g. more than 8 million RDF statements for the English Wikipedia version alone), leading to astonishing query answering possibilities (such as for the title question). We analyze the quality of the extracted content, and propose strategies for quality improvements with just minor modifications of the wiki systems being currently used.

Machine-understandable data constitutes the foundation for the Semantic Web. This paper presents a viable way for authoring and annotating Semantic Documents on the desktop. In our approach, the PDF file format is the container for document semantics, being able to store both the content and the related metadata in a single file. To achieve this, we provide a framework (SALT - Semantically Annotated ), that extends the writing environment and supports the creation of metadata for scientific publications. SALT allows the author to create metadata concurrently, i.e. while in the process of writing a document. We discuss some of the requirements which have to be met when developing such a support for creating semantic documents. In addition, we describe a usage scenario to show the feasability and benefit of our approach.

Annotea provides an annotation protocol to support collaborative Semantic Web-based annotation of digital resources accessible through the Web. It provides a model whereby a user may attach supplementary information to a resource or part of a resource in the form of: either a simple textual comment; a hyperlink to another web page; a local file; or a semantic tag extracted from a formal ontology and controlled vocabulary. Hence, annotations can be used to attach subjective notes, comments, rankings, queries or tags to enable semantic reasoning across web resources. More recently, tabbed browsers and specific annotation tools, allow users to view several resources (e.g., images, video, audio, text, HTML, PDF) simultaneously in order to carry out side-by-side comparisons. In such scenarios, users frequently want to be able to create and annotate a link or relationship between two or more objects or between segments within those objects. For example, a user might want to create a link between a scene in an original film and the corresponding scene in a remake and attach an annotation to that link. Based on past experiences gained from implementing Annotea within different communities in order to enable knowledge capture, this paper describes and compares alternative ways in which the Annotea Schema may be extended for the purpose of annotating links between multiple resources (or segments of resources). It concludes by identifying and recommending an optimum approach which will enhance the power, flexibility and applicability of Annotea in many domains.

Semantic Web technologies are finally, after a few years of infancy, truly entering the business world to support the growing needs of computer aided information selection and processing. There are already quite well-defined development processes and methods in the software engineering field to handle the construction of large scale and complex enterprise systems, and to reuse knowledge in different software domains patterns are considered to be common practise. Patterns can be described on different levels of abstraction, but the patterns in the focus of this paper are on the software architecture level. In this paper we present a definition of the notion ”ontology application pattern”, as a special form of software architecture patterns describing an ontology-based system. We also show how such patterns, as well as the description of the pattern instantiations, can be described using a modified architecture description language.

The Semantic Web community has proposed several query languages for RDF before the World Wide Web Consortium started to standardize SPARQL. Due to the declarative nature of the query language, a query engine should be responsible to choose an efficient evaluation strategy. Although all RDF repositories provide query capabilities, some of them require manual interaction to reduce query execution time by several orders of magnitude.

In this paper, we propose the SPARQL query graph model (SQGM) supporting all phases of query processing. On top of the SQGM we defined transformations rules to simplify and to rewrite a query. Based on these rules we developed heuristics to achieve an efficient query execution plan. Experiments illustrate the potential of our approach.