Combining KARL and CRLM for designing vertical transportation systems

Poeck, Karsten; Fensel, Dieter; Landes, Dieter; Angele, Jürgen

doi:10.1006/ijhc.1996.0021

Cited by 13 publications

(6 citation statements)

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“…• PCM-based methods assume constraints to be defined upfront, and to remain unchanged over the course of the reasoning process. To the best of our knowledge, PCM-based methods (such as Poeck et al, 1996;Grimnes & Aamodt, 1996;ten Teije & van Harmelen, 2004;Schreiber & Terpstra, 1996) use a set of unchanging constraints to trigger modifications. These constraints are assumed to be a static given at the start of the reasoning process.…”

Section: Pcm 2 Compared To Pcm Methodsmentioning

confidence: 99%

e3service: An ontology for needs-driven real-world service bundling in a multi-supplier setting

Kinderen¹,

Leenheer

Gordijn

et al. 2013

Applied Ontology

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Businesses increasingly offer their services electronically via the Web. Take for example an Internet Service Provider. An ISP offers a variety of services, including raw bandwidth, IP connectivity, and Domain Name resolution. Although in some cases a single service already satisfies a customer need, in many situations a customer need is so complex that a bundle of services is needed to satisfy the need, as with the ISP example. In principle, each service in a bundle can be provisioned by a different supplier. This paper proposes an ontology, e 3 service, that can be used to formally capture customer needs, services, and multi-supplier service bundles of these. In addition, this paper contributes a process called PCM 2 to reason with the ontology. First, a customer need is identified for which desired consequences are elicited. Then, the desired set of consequences is matched with consequences associated with services. The matching process results in a service bundle, satisfying the customer need, containing services that each can be provided by different suppliers. PCM 2 is inspired by a family of formal reasoning methods called Propose-Critique-Modify (PCM). However, whereas PCM methods emphasize solution generation from a given set of requirements, our reasoning process treats the space of requirements as a first class citizen. Hence PCM 2 : the requirements space and solution space are equally important. How the reasoning and matching process practically works, is illustrated by an industry strength case study in the healthcare domain. S. De Kinderen et al. / An ontology for needs-driven service bundling in a multi-supplier settingName resolution; but additional services, such as an email box, chat box, Voice over IP (VoIP), or Instant Messaging (IM) may be offered as well.Although many customers may deal with just one ISP to have all their Internet-related needs satisfied, this is not always strictly necessary or possible. The above-mentioned basic ISP services may each be provided in their own right, and so by different suppliers. For example, the customer may obtain raw bandwidth from supplier S 1 , IP connectivity and Domain Name resolution from supplier S 2 , and an email box from yet another supplier. Partnering enables suppliers to cooperate and satisfy complex customer needs they never could have done on their own in a flexible way. This phenomenon is increasingly observed in e-commerce settings, especially when small enterprises come into play (see e.g. Tapscott et al., 2000).Multi-supplier bundles often satisfy customer's need much better and cheaper, as opposed to a single supplier bundle. Moreover, fixed single supplier service offerings often contains unwanted services such as an ill-functioning spam filter of an email service with poor storage capabilities. Given this explosion of possible combinations, it is a technological challenge to provide automated support for composing the most optimal bundle in response to an individual's unique needs, and by doing so build long-term partnerships among ...

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Section: Pcm 2 Compared To Pcm Methodsmentioning

confidence: 99%

e3service: An ontology for needs-driven real-world service bundling in a multi-supplier setting

Kinderen¹,

Leenheer

Gordijn

et al. 2013

Applied Ontology

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“…In the meantime MIKE has been applied to more than a dozen applications including the mentioned application for selecting techniques for dismantling buildings (Fichtner et al, 1995), an application for supporting a help desk service for users of a communication network (Waarle, 1995), an application for designing artefacts in engineering tasks (Poeck et al, 1996), and an application for determining optimal shift-systems for various types of companies (Gissel & Knauth, 1997).…”

Section: Resultsmentioning

confidence: 99%

Developing Knowledge-Based Systems with MIKE

Angele¹,

Fensel²,

Landes

et al. 1998

Domain Modelling for Interactive Systems Design

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The paper describes the MIKE (Model-based and Incremental Knowledge Engineering) approach for developing knowledge-based systems. MIKE integrates semiformal and formal specification techniques together with prototyping into a coherent framework. All activities in the building process of a knowledge-based system are embedded in a cyclic process model. For the semiformal representation we use a hypermedia-based formalism which serves as a communication basis between expert and knowledge engineer during knowledge acquisition. The semiformal knowledge representation is also the basis for formalization, resulting in a formal and executable model specified in the Knowledge Acquisition and Representation Language (KARL). Since KARL is executable, the model of expertise can be developed and validated by prototyping. A smooth transition from a semiformal to a formal specification and further on to design is achieved because all the description techniques rely on the same conceptual model to describe the functional and non-functional aspects of the system. Thus, the system is thoroughly documented at different description levels, each of which focuses on a distinct aspect of the entire development effort. Traceability of requirements is supported by linking the different models to each other.

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“…stanford.edu/~petrie/caia.html), and Dieter Fensel, of the Digital Enterprise Research Institute (DERI; http://www. deri.org), has helped design such workshop challenge problems for elevator design 1 and online product clas-sification. 2 Both problems are often cited and have generated good work.…”

Section: Crossing the Cultural Dividementioning

confidence: 99%

Pragmatic semantic unification

Petrie

2005

IEEE Internet Comput.

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Combining KARL and CRLM for designing vertical transportation systems

Cited by 13 publications

References 0 publications

e3service: An ontology for needs-driven real-world service bundling in a multi-supplier setting

e3service: An ontology for needs-driven real-world service bundling in a multi-supplier setting

Developing Knowledge-Based Systems with MIKE

Pragmatic semantic unification

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