The KRAFT Architecture for Knowledge Fusion and Transformation

Preece, Alun; Hui, Kit; Gray, Alex; Marti, Philippe; Bench‐Capon, Trevor; Jones, Dean M.; Cui, Zhan

doi:10.1007/978-1-4471-0745-3_2

Cited by 39 publications

(30 citation statements)

References 4 publications

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“…The KRAFT system uses constraints to check whether information from heterogeneous sources can be merged [49,26]. If knowledge satisfies the constraints, then the knowledge can be used.…”

Section: Discussionmentioning

confidence: 99%

Fusion rules for merging uncertain information

Hunter

Liu

2006

Information Fusion

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In previous papers, we have presented a logic-based framework based on fusion rules for merging structured news reports. Structured news reports are XML documents, where the textentries are restricted to individual words or simple phrases, such as names and domain-specific terminology, and numbers and units. We assume structured news reports do not require natural language processing. Fusion rules are a form of scripting language that define how structured news reports should be merged. The antecedent of a fusion rule is a call to investigate the information in the structured news reports and the background knowledge, and the consequent of a fusion rule is a formula specifying an action to be undertaken to form a merged report. It is expected that a set of fusion rules is defined for any given application. In this paper we extend the approach to handling probability values, degrees of beliefs, or necessity measures associated with textentries in the news reports. We present the formal definition for each of these types of uncertainty and explain how they can be handled using fusion rules. We also discuss the methods of detecting inconsistencies among sources.

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“…The KRAFT system uses constraints to check whether information from heterogeneous sources can be merged [49,26]. If knowledge satisfies the constraints, then the knowledge can be used.…”

Section: Discussionmentioning

confidence: 99%

Fusion rules for merging uncertain information

Hunter

Liu

2006

Information Fusion

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“…For example, Multiagent Manufacturing Agile Scheduling Systems for Virtual Enterprises (MASSYVE) [18] focuses on agile scheduling, X-CITTIC (Planning and Control System for Semiconductor Virtual Enterprises) [22] concentrates on planning and controlling and STEP and the Virtual Enterprise (SAVE) 4 focuses on data modelling for VE. Furthermore, earlier research in enterprise-wide business management systems has focussed on the management (through automated negotiation) of business processes within a static organisational structure-ADEPT [11]-and models and techniques for information interchange-KRAFT [17].…”

Section: Related Workmentioning

confidence: 99%

Agent-based formation of virtual organisations

Norman

Preece

Chalmers

et al. 2004

Knowledge-Based Systems

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135

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Virtual organisations (VOs) are composed of a number of individuals, departments or organisations each of which has a range of capabilities and resources at their disposal. These VOs are formed so that resources may be pooled and services combined with a view to exploiting a perceived market niche. However, in the modern commercial environment it is essential to respond rapidly to changes in the market to remain competitive. Thus, there is a need for robust, agile, flexible systems to support the process of VO management. Within the CONOISE (www.conoise.org) project, agent-based models and techniques are being developed for the automated formation and maintenance of virtual organisations. In this paper we focus on the former, namely how an effective VO may be formed rapidly for a specified purpose. q

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“…Information integration can be subdivided into two different types. On the one hand, ontologies are mapped together in order to integrate concepts in two or more domain of interest (Inter-Ontology mapping) (Kashyap and Sheth, 1996;Mena et al, 1996;Preece et al, 2000;Stuckenschmidt and Wache, 2000). This type of integration is not the aim of this paper.…”

Section: Semantic Web Technologymentioning

confidence: 99%

Semantic Annotation of Existing Geo-Datasets: A Case Study of Disaster Response in Netherlands

Mobasheri

Oosterom

Zlatanova

et al. 2013

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Use of relevant geo-information is one of the important issues for performing different tasks and processes in disaster response phase. In order to save time and cost, services could be employed for integrating and extracting relevant up-to-date geo-information. For this purpose, semantics of geo-information should be explicitly defined. This paper presents our initial results in applying an approach for semantic annotation of existing geo-datasets. In this research the process of injecting semantic descriptions into geodatasets (information integration) is called semantic annotation. A web system architecture is presented and the process of semantic annotation is presented by using the Meta-Annotation approach. The approach is elaborated by providing an example in disaster response which utilizes geo-datasets in CityGML format and further two languages of semantic web technology: RDF and Notation3.

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The KRAFT Architecture for Knowledge Fusion and Transformation

Cited by 39 publications

References 4 publications

Fusion rules for merging uncertain information

Fusion rules for merging uncertain information

Agent-based formation of virtual organisations

Semantic Annotation of Existing Geo-Datasets: A Case Study of Disaster Response in Netherlands

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