DOCUMENT-ORIENTED DEVELOPMENT OF CONTENT-INTENSIVE APPLICATIONS

Author(s):  
JOSÉ LUIS SIERRA ◽  
BALTASAR FERNÁNDEZ-MANJÓN ◽  
ALFREDO FERNÁNDEZ-VALMAYOR ◽  
ANTONIO NAVARRO

In this paper we promote a document-oriented approach to the development of content-intensive applications (i.e., applications that critically depend on the informational contents and on the characterization of the contents' structure). This approach is the result of our experience as developers in the educational and in the hypermedia domains, as well as in the domain of knowledge-based systems. The main reason for choosing the document-oriented approach is to make it easier for domain experts to comprehend the elements that represent the main application's features. Among these elements are: the application's contents, the application's customizable properties including those of its interface, and the structure of all this information. Therefore, in our approach, these features are represented by means of a set of application documents, which are marked up using a suitable descriptive Domain-Specific Markup Language (DSML). If this goal is fully accomplished, the application itself can be automatically produced by processing those documents with a suitable processor for the DSML defined. The document-oriented development enhances the production and maintenance of content-intensive applications, because the applications' features are described in the form of human-readable and editable documents, understandable by domain experts and suitable for automatic processing. Nevertheless, the main drawbacks of the approach are the planning overload of the whole production process and the costs of the provision and maintenance of the DSMLs and their processors. These drawbacks can be palliated by adopting an incremental strategy for the production and maintenance of the applications and also for the definition and the operationalization of the DSMLs.

1995 ◽  
Vol 34 (01/02) ◽  
pp. 25-39 ◽  
Author(s):  
G. Lanzola ◽  
S. Quaglini ◽  
M. Stefanelli

Abstract:Knowledge-based systems (KBS) have been proposed to solve a large variety of medical problems. A strategic issue for KBS development and maintenance are the efforts required for both knowledge engineers and domain experts. The proposed solution is building efficient knowledge acquisition (KA) tools. This paper presents a set of KA tools we are developing within a European Project called GAMES II. They have been designed after the formulation of an epistemological model of medical reasoning. The main goal is that of developing a computational framework which allows knowledge engineers and domain experts to interact cooperatively in developing a medical KBS. To this aim, a set of reusable software components is highly recommended. Their design was facilitated by the development of a methodology for KBS construction. It views this process as comprising two activities: the tailoring of the epistemological model to the specific medical task to be executed and the subsequent translation of this model into a computational architecture so that the connections between computational structures and their knowledge level counterparts are maintained. The KA tools we developed are illustrated taking examples from the behavior of a KBS we are building for the management of children with acute myeloid leukemia.


Author(s):  
Ram Kumar ◽  
Shailesh Jaloree ◽  
R. S. Thakur

Knowledge-based systems have become widespread in modern years. Knowledge-base developers need to be able to share and reuse knowledge bases that they build. As a result, interoperability among different knowledge-representation systems is essential. Domain ontology seeks to reduce conceptual and terminological confusion among users who need to share various kind of information. This paper shows how these structures make it possible to bridge the gap between standard objects and Knowledge-based Systems.


Terminology ◽  
2005 ◽  
Vol 11 (1) ◽  
pp. 55-81 ◽  
Author(s):  
Lee Gillam ◽  
Mariam Tariq ◽  
Khurshid Ahmad

This paper discusses a method for corpus-driven ontology design: extracting conceptual hierarchies from arbitrary domain-specific collections of texts. These hierarchies can form the basis for a concept-oriented (onomasiological) terminology collection, and hence may be used as the basis for developing knowledge-based systems using ontology editors. This reference to ontology is explored in the context of collections of terms. The method presented is a hybrid of statistical and linguistic techniques, employing statistical techniques initially to elicit a conceptual hierarchy, which is then augmented through linguistic analysis. The result of such an extraction may be useful in information retrieval, knowledge management, or in the discipline of terminology science itself.


Author(s):  
Sabine Moisan

This paper investigates software engineering techniques for designing and reengineering knowledge-based system generators, focusing on inference engines and domain specific languages. Indeed, software development of knowledge-based systems is a difficult task. We choose a software engineering approach to favor code reuse, evolution, and maintenance. We propose a software platform named Lama to design the different elements necessary to produce a knowledge-based system. This platform offers software toolkits (mainly component frameworks) to build interfaces, inference engines, and expert languages. We have used the platform to build several KBS generators for various tasks (planning, classification, model calibration) in different domains. The approach appears well fitted to knowledge-based system generators; it allows developers a significant gain in time, as well as it improves software readability and safeness.


Author(s):  
José L. Sierra ◽  
Baltasar Fernández-Manjón ◽  
Alfredo Fernández-Valmayor ◽  
Antonio Navarro

Author(s):  
Sabine Moisan

This article investigates software engineering techniques for designing and reengineering knowledge-based system generators, focusing on inference engines and domain specific languages. Indeed, software development of knowledge-based systems is a difficult task. We choose a software engineering approach to favor code reuse, evolution, and maintenance. We propose a software platform named Lama to design the different elements necessary to produce a knowledge-based system. This platform offers software toolkits (mainly component frameworks) to build interfaces, inference engines, and expert languages. We have used the platform to build several KBS generators for various tasks (planning, classification, model calibration) in different domains. The approach appears well fitted to knowledge-based system generators; it allows developers a significant gain in time, as well as it improves software readability and safeness.


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