8,235 research outputs found
Design and implementation of a filter engine for semantic web documents
This report describes our project that addresses the challenge of changes in the semantic web. Some studies have already been done for the so-called adaptive semantic web, such as applying inferring rules. In this study, we apply the technology of Event Notification System (ENS). Treating changes as events, we
developed a notification system for such events
IVOA Recommendation: VOResource: an XML Encoding Schema for Resource Metadata Version 1.03
This document describes an XML encoding standard for IVOA Resource Metadata,
referred to as VOResource. This schema is primarily intended to support
interoperable registries used for discovering resources; however, any
application that needs to describe resources may use this schema. In this
document, we define the types and elements that make up the schema as
representations of metadata terms defined in the IVOA standard, Resource
Metadata for the Virtual Observatory [Hanicsh et al. 2004]. We also describe
the general model for the schema and explain how it may be extended to add new
metadata terms and describe more specific types of resources
IVOA Recommendation: Resource Metadata for the Virtual Observatory Version 1.12
An essential capability of the Virtual Observatory is a means for describing
what data and computational facilities are available where, and once
identified, how to use them. The data themselves have associated metadata
(e.g., FITS keywords), and similarly we require metadata about data collections
and data services so that VO users can easily find information of interest.
Furthermore, such metadata are needed in order to manage distributed queries
efficiently; if a user is interested in finding x-ray images there is no point
in querying the HST archive, for example. In this document we suggest an
architecture for resource and service metadata and describe the relationship of
this architecture to emerging Web Services standards. We also define an initial
set of metadata concepts
Entity Ranking on Graphs: Studies on Expert Finding
Todays web search engines try to offer services for finding various information in addition to simple web pages, like showing locations or answering simple fact queries. Understanding the association of named entities and documents is one of the key steps towards such semantic search tasks. This paper addresses the ranking of entities and models it in a graph-based relevance propagation framework. In particular we study the problem of expert finding as an example of an entity ranking task. Entity containment graphs are introduced that represent the relationship between text fragments on the one hand and their contained entities on the other hand. The paper shows how these graphs can be used to propagate relevance information from the pre-ranked text fragments to their entities. We use this propagation framework to model existing approaches to expert finding based on the entity's indegree and extend them by recursive relevance propagation based on a probabilistic random walk over the entity containment graphs. Experiments on the TREC expert search task compare the retrieval performance of the different graph and propagation models
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