Dynamic evaluation of the development process of knowledge-based information systems

Beydoun, Ghassan; Hoffmann, Achim

doi:10.1007/s10115-012-0491-z

Cited by 3 publications

(3 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, a structured and understood knowledge representation is required to resolve existing inconsistencies. For example, using incremental approaches based on interactions between an expert and a data stream input can be used [4,10].…”

Section: Ontology-based Methodological Development Of Masmentioning

confidence: 99%

Centering ontologies in agent oriented software engineering processes

Beydoun

Low

2016

Complex Intell. Syst.

Self Cite

View full text Add to dashboard Cite

A plethora of Multi Agent Systems (MAS) development methodologies exists and all compete for prominence. This paper advocates unification of best of breed activities from these methodologies and examines two existing approaches for unifying access to them. It proposes an alternative approach that focusses on the use of domain knowledge through ontologies as offering the best potential for unifying access to them. The reliance on ontologies will provide flexibility in the process and workproducts use within the methodology. The focus on domain knowledge will reduce the number of mandatory methodological tasks and at the same time create scope for reuse with respect to both system designs and components. The paper will further sketch and argue for a full software development lifecycle for MAS where ontologies expressing domain knowledge are the central artifacts.

show abstract

Section: Ontology-based Methodological Development Of Masmentioning

confidence: 99%

Centering ontologies in agent oriented software engineering processes

Beydoun

Low

2016

Complex Intell. Syst.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Hence, the process of checking inconsistencies is also recursive. In [9], we presented why the number of inconsistencies is too small to have a major impact to the cost of the total knowledge acquisition process.…”

Section: Rdr and Nrdr Incremental Processesmentioning

confidence: 99%

“…The process often gets bogged down during the design stage as concrete models are not readily available and modeling from scratch may be too expensive. This problem is stultified using incremental approaches based on interactions between an expert and a data stream input [9]. The performance of an evolving prototype is improved with iterative development.…”

Section: Introductionmentioning

confidence: 99%

Constructing enhanced default theories incrementally

Beydoun

Hoffmann

Gill

2017

Complex Intell. Syst.

Self Cite

View full text Add to dashboard Cite

The main difference between various formalisms of non-monotonic reasoning is the representation of nonmonotonic rules. In default logic, they are represented by special expressions called defaults. In default logic, commonsense knowledge about the world is represented as a set of named defaults. The use of defaults is popular because they reduce the complexity of the representation, and they are sufficient for knowledge representation in many naturally occurring contexts. This paper offers an incremental process to acquire defaults from human experts directly and at the same time it provides added semantics to defaults by adding priorities to defaults and creating additional relations between them. The paper uses an existing incremental framework, NRDR, to generate these defaults. This framework is chosen as it not only enables incremental context driven formulation of defaults, but also allows experts to introduce their own domain terms. In choosing this framework, the paper broadens its utility.

show abstract

On the difficulty of automatically detecting irony: beyond a simple case of negation

Reyes¹,

Rosso

2013

Knowl Inf Syst

View full text Add to dashboard Cite

Rosso, P. (2014Abstract. It is well-known that irony is one of the most subtle devices used to, in a refined way and without a negation marker, deny what is literally said. As such, its automatic detection would represent valuable knowledge regarding tasks as diverse as sentiment analysis, information extraction, or decision making. The research described in this article is focused on identifying key values of components to represent underlying characteristics of this linguistic phenomenon. In absence of a negation marker, we focus on representing the core of irony by means of three conceptual layers. These layers involve 8 different textual features. By representing four available data sets with these features, we try to find hints about how to deal with this unexplored task from a computational point of view. Our findings are assessed by human annotators in two strata: isolated sentences and entire documents. The results show how complex and subjective the task of automatically detecting irony could be.

show abstract

Dynamic evaluation of the development process of knowledge-based information systems

Cited by 3 publications

References 30 publications

Centering ontologies in agent oriented software engineering processes

Centering ontologies in agent oriented software engineering processes

Constructing enhanced default theories incrementally

On the difficulty of automatically detecting irony: beyond a simple case of negation

Contact Info

Product

Resources

About