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Two-fold Semantic Web service matchmaking – applying ontology mapping for service discovery
Semantic Web Services (SWS) aim at the automated discovery and orchestration of Web services on the basis of comprehensive, machine-interpretable semantic descriptions. Since SWS annotations usually are created by distinct SWS providers, semantic-level mediation, i.e. mediation between concurrent semantic representations, is a key requirement for SWS discovery. Since semantic-level mediation aims at enabling interoperability across heterogeneous semantic representations, it can be perceived as a particular instantiation of the ontology mapping problem. While recent SWS matchmakers usually rely on manual alignments or subscription to a common ontology, we propose a two-fold SWS matchmaking approach, consisting of (a) a general-purpose semantic-level mediator and (b) comparison and matchmaking of SWS capabilities. Our semantic-level mediation approach enables the implicit representation of similarities across distinct SWS by grounding service descriptions in so-called Mediation Spaces (MS). Given a set of SWS and their respective grounding, a SWS matchmaker automatically computes instance similarities across distinct SWS ontologies and matches the request to the most suitable SWS. A prototypical application illustrates our approach
Interoperable multimedia metadata through similarity-based semantic web service discovery
The increasing availability of multimedia (MM) resources, Web services as well as content, on the Web raises the need to automatically discover and process resources out of distributed repositories. However, the heterogeneity of applied metadata schemas and vocabularies – ranging from XML-based schemas such as MPEG-7 to formal knowledge representation approaches – raises interoperability problems. To enable MM metadata interoperability by means of automated similarity-computation, we propose a hybrid representation approach which combines symbolic MM metadata representations with a grounding in so-called Conceptual Spaces (CS). In that, we enable automatic computation of similarities across distinct metadata vocabularies and schemas in terms of spatial distances in shared CS. Moreover, such a vector-based approach is particularly well suited to represent MM metadata, given that a majority of MM parameters is provided in terms of quantified metrics. To prove the feasibility of our approach, we provide a prototypical implementation facilitating similarity-based discovery of publicly available MM services, aiming at federated MM content retrieval out of heterogeneous repositories
The pragmatic proof: hypermedia API composition and execution
Machine clients are increasingly making use of the Web to perform tasks. While Web services traditionally mimic remote procedure calling interfaces, a new generation of so-called hypermedia APIs works through hyperlinks and forms, in a way similar to how people browse the Web. This means that existing composition techniques, which determine a procedural plan upfront, are not sufficient to consume hypermedia APIs, which need to be navigated at runtime. Clients instead need a more dynamic plan that allows them to follow hyperlinks and use forms with a preset goal. Therefore, in this paper, we show how compositions of hypermedia APIs can be created by generic Semantic Web reasoners. This is achieved through the generation of a proof based on semantic descriptions of the APIs' functionality. To pragmatically verify the applicability of compositions, we introduce the notion of pre-execution and post-execution proofs. The runtime interaction between a client and a server is guided by proofs but driven by hypermedia, allowing the client to react to the application's actual state indicated by the server's response. We describe how to generate compositions from descriptions, discuss a computer-assisted process to generate descriptions, and verify reasoner performance on various composition tasks using a benchmark suite. The experimental results lead to the conclusion that proof-based consumption of hypermedia APIs is a feasible strategy at Web scale.Peer ReviewedPostprint (author's final draft
An XRI naming system for dynamic and federated clouds: a performance analysis
Abstract
Cloud platforms are dynamic, self-optimizing, continuously changing environments where resources can be composed with other ones in order to provide many types of services to their users, e.g., companies, governments, organizations, and desktop/mobile clients. In order to enable cloud platforms to manage and control their assets, they need to name, identify, and resolve their virtual resources in different operating contexts. In such a scenario, naming, resource location, and information retrieval raise several issues regarding name space management. This paper aims to propose a standard practice for the implementation of a cloud naming system based on the eXtensible Resource Identifier (XRI) technology. More specifically, by means of the development of a Cloud Name Space Management (CNSM) front-end interacting with the OpenXRI architecture, we investigate its performance simulating typical cloud name space management tasks
K-Space at TRECVID 2008
In this paper we describe K-Space’s participation in
TRECVid 2008 in the interactive search task. For 2008
the K-Space group performed one of the largest interactive
video information retrieval experiments conducted
in a laboratory setting. We had three institutions participating
in a multi-site multi-system experiment. In
total 36 users participated, 12 each from Dublin City
University (DCU, Ireland), University of Glasgow (GU,
Scotland) and Centrum Wiskunde and Informatica (CWI,
the Netherlands). Three user interfaces were developed,
two from DCU which were also used in 2007 as well as
an interface from GU. All interfaces leveraged the same
search service. Using a latin squares arrangement, each
user conducted 12 topics, leading in total to 6 runs per
site, 18 in total. We officially submitted for evaluation 3
of these runs to NIST with an additional expert run using
a 4th system. Our submitted runs performed around
the median. In this paper we will present an overview of
the search system utilized, the experimental setup and a
preliminary analysis of our results
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