The 'what' and 'how' of learning in design, invited paper

Previous experiences hold a wealth of knowledge which we often take for granted and use unknowingly through our every day working lives. In design, those experiences can play a crucial role in the success or failure of a design project, having a great deal of influence on the quality, cost and development time of a product. But how can we empower computer based design systems to acquire this knowledge? How would we use such systems to support design? This paper outlines some of the work which has been carried out in applying and developing Machine Learning techniques to support the design activity; particularly in utilising previous designs and learning the design process

Formal Concept Analysis and Resolution in Algebraic Domains

We relate two formerly independent areas: Formal concept analysis and logic of domains. We will establish a correspondene between contextual attribute logic on formal contexts resp. concept lattices and a clausal logic on coherent algebraic cpos. We show how to identify the notion of formal concept in the domain theoretic setting. In particular, we show that a special instance of the resolution rule from the domain logic coincides with the concept closure operator from formal concept analysis. The results shed light on the use of contexts and domains for knowledge representation and reasoning purposes.Comment: 14 pages. We have rewritten the old version according to the suggestions of some referees. The results are the same. The presentation is completely differen

Bottom-up construction of ontologies

Presents a particular way of building ontologies that proceeds in a bottom-up fashion. Concepts are defined in a way that mirrors the way their instances are composed out of smaller objects. The smaller objects themselves may also be modeled as being composed. Bottom-up ontologies are flexible through the use of implicit and, hence, parsimonious part-whole and subconcept-superconcept relations. The bottom-up method complements current practice, where, as a rule, ontologies are built top-down. The design method is illustrated by an example involving ontologies of pure substances at several levels of detail. It is not claimed that bottom-up construction is a generally valid recipe; indeed, such recipes are deemed uninformative or impossible. Rather, the approach is intended to enrich the ontology developer's toolki

Combining factual and heuristic knowledge in knowledge acquisition

A knowledge acquisition technique that combines heuristic and factual knowledge represented as two hierarchies is described. These ideas were applied to the construction of a knowledge acquisition interface to the Expert System Analyst (OPERA). The goal of OPERA is to improve the operations support of the computer network in the space shuttle launch processing system. The knowledge acquisition bottleneck lies in gathering knowledge from human experts and transferring it to OPERA. OPERA's knowledge acquisition problem is approached as a classification problem-solving task, combining this approach with the use of factual knowledge about the domain. The interface was implemented in a Symbolics workstation making heavy use of windows, pull-down menus, and other user-friendly devices

Facets, Tiers and Gems: Ontology Patterns for Hypernormalisation

There are many methodologies and techniques for easing the task of ontology building. Here we describe the intersection of two of these: ontology normalisation and fully programmatic ontology development. The first of these describes a standardized organisation for an ontology, with singly inherited self-standing entities, and a number of small taxonomies of refining entities. The former are described and defined in terms of the latter and used to manage the polyhierarchy of the self-standing entities. Fully programmatic development is a technique where an ontology is developed using a domain-specific language within a programming language, meaning that as well defining ontological entities, it is possible to add arbitrary patterns or new syntax within the same environment. We describe how new patterns can be used to enable a new style of ontology development that we call hypernormalisation