Use Of Domain Knowledge Research Articles

Software re-engineering and reuse from a Japanese point of view

It is generally recognized that software re-engineering and reuse technologies are vitally important and a highly effective means of alleviating the so-called ‘software crisis’. The paper discusses various methodologies and tools in a review of related research and development efforts as well as commercialized products, mainly in Japan, and places them in a consolidated perspective, giving some examples of those items considered as particularly interesting from a Japanese point of view. In Japan, the concept of treating reusable pieces of software as parts has been very effectively employed, and tree-structured graphical charts are widely used in both forward and reverse software engineering. An increasing emphasis is on the use of domain knowledge and object-oriented methodologies.

Can Decision Analysis Define the Goals of Training?

An appealing goal in the training of decision makers is the development of formal reasoning skills based on decision analysis. Such techniques are applicable to virtually any problem and are guaranteed to be formally consistent. Behavioral evidence regarding “heuristics and biases,” however, suggests that deviations from such methods are systematic, hard to eliminate, and characteristic of both novices and experts in a number of real-world domains. Would training in formal methods to avoid biases (if it were possible) produce an improvement in the quality of decision making? There are reasons to believe that it would not. “Biases” may in fact be inescapable by-products of the knowledge structures and problem-solving methods that make experienced decision makers effective. Inconsistencies in judgments and choices (1) may simply not matter much in real-world domains; (2) may be corrected in dynamic environments; and (3) may be offset in any case by the advantages of effective use of decision-maker knowledge. Moreover, the identification of biases based on the current experimental literature may itself be mistaken, due to incomplete or otherwise inadequate models. Effective performance in most domains is the result of (a) a reportoire of recognition-based responses, and (b) a set of meta-recognitional strategies that facilitate recognition and validate the results. In training based on these concepts, “errors” are avoided by acquiring and making the most effective use of domain knowledge, and by adapting to feedback, changes in the situation, and shortcomings in one's current approach as they appear.

Geometric reasoning for constructing 3D scene descriptions from images

There are many applications for a vision system which derives a three-dimensional model of a scene from one or more images and stores the model for easy retrieval and matching. The derivation of a 3D model of a scene involves transformations between four levels of representation: images, 2D features, 3D structures, and 3D geometric models. Geometric reasoning is used to perform these transformations, as well as for the eventual model matching. Since the image formation process is many-to-one, the problem of deriving 3D features from 2D features is ill-constrained. Additional constraints may be derived from knowledge of the domain from which the images were taken. The 3D MOSAIC system has successfully used domain specific knowledge to drive the geometric reasoning necessary to acquire 3D models for complex real-world urban scenes. To generalize this approach, a framework for the representation and use of domain knowledge for geometric reasoning for vision is proposed.

Knowledge-based approach to requirements engineering using method and domain knowledge

Within information systems development the correct capture of user requirements plays a central role in the construction of effective and flexible systems. This paper views requirements specification as primarily a knowledge intensive activity, and the work reported here follows the premise that the next generation of requirements engineering environments will be knowledge-based. The paper argues that these environments will need to make use of two types of ‘requirements analysis’ knowledge, namely method and domain knowledge. Method knowledge relates to the design discipline adopted by a systems analyst in order to develop a requirements specification. Much of this knowledge relates to the formalism underlying a particular development approach. The paper discusses how such knowledge may be used to assist analysts, and shows how development methods may be analysed in terms of their conceptual formalisms. It argues that systems analysts make extensive use of domain knowledge when attempting to specify requirements, and analyses the characteristics of this knowledge. A knowledge-based requirements specification environment currently under development is also presented.