Search (10 results, page 1 of 1)

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Date

11. 2.2011 18:22:25

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Abstract

An ontology is "an explicit conceptualization of a domain of discourse, and thus provides a shared and common understanding of the domain." We have been producing ontologies for millennia to understand and explain our rationale and environment. From Plato's philosophical framework to modern day classification systems, ontologies are, in most cases, the product of extensive analysis and categorization. Only recently has the process of building ontologies become a research topic of interest. Today, ontologies are built very much ad-hoc. A terminology is first developed providing a controlled vocabulary for the subject area or domain of interest, then it is organized into a taxonomy where key concepts are identified, and finally these concepts are defined and related to create an ontology. The intent of this paper is to show that domain analysis methods can be used for building ontologies. Domain analysis aims at generic models that represent groups of similar systems within an application domain. In this sense, it deals with categorization of common objects and operations, with clear, unambiguous definitions of them and with defining their relationships.

Type

a

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Abstract

This paper discusses the use of wiki technology to provide a navigation structure for a collection of newspaper clippings. We overview the architecture of the wiki, discuss the navigation structure and pose the question: is the navigation structure an index, and if so, what type, or is it just a linkage structure or topic map. Does such a distinction really matter? Are these definitions in reality function based?

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Abstract

We scho how the beenfits of the view-based search method, developed within the information retrieval community, can be extended with ontology-based search, developed within the Semantic Web community, and with semantic recommendations. As a proof of the concept, we have implemented an ontology-and view-based search engine and recommendations system Ontogaotr for RDF(S) repositories. Ontogator is innovative in two ways. Firstly, the RDFS.based ontologies used for annotating metadata are used in the user interface to facilitate view-based information retrieval. The views provide the user with an overview of the repositorys contents and a vocabulary for expressing search queries. Secondlyy, a semantic browsing function is provided by a recommender system. This system enriches instance level metadata by ontologies and provides the user with links to semantically related relevant resources. The semantic linkage is specified in terms of logical rules. To illustrate and discuss the ideas, a deployed application of Ontogator to a photo repository of the Helsinki University Museum is presented.

Type

a

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Abstract

Semantic Search has become an active research of Semantic Web in recent years. The classification methodology plays a pretty critical role in the beginning of search process to disambiguate irrelevant information. However, the applications related to Folksonomy suffer from many obstacles. This study attempts to eliminate the problems resulted from Folksonomy using existing semantic technology. We also focus on how to effectively integrate heterogeneous ontologies over the Internet to acquire the integrity of domain knowledge. A faceted logic layer is abstracted in order to strengthen category framework and organize existing available ontologies according to a series of steps based on the methodology of faceted classification and ontology construction. The result showed that our approach can facilitate the integration of inconsistent or even heterogeneous ontologies. This paper also generalizes the principles of picking appropriate facets with which our facet browser completely complies so that better semantic search result can be obtained.

Type

a

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Abstract

An increasing number of applications rely on RDF, OWL2, and SPARQL for storing and querying data. SPARQL, however, is not targeted towards end-users, and suitable query interfaces are needed. Faceted search is a prominent approach for end-user data access, and several RDF-based faceted search systems have been developed. There is, however, a lack of rigorous theoretical underpinning for faceted search in the context of RDF and OWL2. In this paper, we provide such solid foundations. We formalise faceted interfaces for this context, identify a fragment of first-order logic capturing the underlying queries, and study the complexity of answering such queries for RDF and OWL2 profiles. We then study interface generation and update, and devise efficiently implementable algorithms. Finally, we have implemented and tested our faceted search algorithms for scalability, with encouraging results.

Type

a

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Type

a

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Abstract

The formal structure of the information on the Semantic Web lends itself to faceted browsing, an information retrieval method where users can filter results based on the values of properties ("facets"). Numerous faceted browsers have been created to browse RDF and Linked Data, but these systems use their own ontologies for defining how data is queried to populate their facets. Since the source data is the same format across these systems (specifically, RDF), we can unify the different methods of describing how to quer the underlying data, to enable compatibility across systems, and provide an extensible base ontology for future systems. To this end, we present FacetOntology, an ontology that defines how to query data to form a faceted browser, and a number of transformations and filters that can be applied to data before it is shown to users. FacetOntology overcomes limitations in the expressivity of existing work, by enabling the full expressivity of SPARQL when selecting data for facets. By applying a FacetOntology definition to data, a set of facets are specified, each with queries and filters to source RDF data, which enables faceted browsing systems to be created using that RDF data.

Type

a

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Abstract

Documents in rich text corpora usually contain multiple facets of information. For example, an article about a specific disease often consists of different facets such as symptom, treatment, cause, diagnosis, prognosis, and prevention. Thus, documents may have different relations based on different facets. Powerful search tools have been developed to help users locate lists of individual documents that are most related to specific keywords. However, there is a lack of effective analysis tools that reveal the multifaceted relations of documents within or cross the document clusters. In this paper, we present FacetAtlas, a multifaceted visualization technique for visually analyzing rich text corpora. FacetAtlas combines search technology with advanced visual analytical tools to convey both global and local patterns simultaneously. We describe several unique aspects of FacetAtlas, including (1) node cliques and multifaceted edges, (2) an optimized density map, and (3) automated opacity pattern enhancement for highlighting visual patterns, (4) interactive context switch between facets. In addition, we demonstrate the power of FacetAtlas through a case study that targets patient education in the health care domain. Our evaluation shows the benefits of this work, especially in support of complex multifaceted data analysis.

Type

a

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Type

a