Invisibility is an inherent and significant problem in the task of developing large software systems. There are no direct solutions to this problem

Although knowledge representation is one of the central and in some ways most familiar concepts in AI, the most fundamental question about it---What is it?---has rarely been answered directly. Numerous papers have lobbied for one or another variety of representation, other papers have argued for various properties a representation should have, while still others have focused on properties that are important to the notion of representation in general. In this paper we go back to basics to address the question directly. We believe that the answer can best be understood in terms of five important and distinctly different roles that a representation plays, each of which places different and at times conflicting demands on the properties a representation should have. We argue that keeping in mind all five of these roles provides a usefully broad perspective that sheds light on some longstanding disputes and can invigorate both research and practice in the field. 1 This report describes res...

Software reuse is one of the most advertised advantages of object-orientation. Inheritance, in all its forms, plays an important part in achieving greater reuse, at all stages of development. Class hierarchies start taking shape at the analysis level, where classes that share application-significant data and application-meaningful external behavior are grouped under more general classes. At the design level, such hierarchies are augmented with implementation classes, and possibly reorganized to take into account implementation factors such as performance or code reuse [22]. Getting the analysis-level hierarchy "right" is very important for the understandability and traceability of the models and the reusability of the resulting code [22]. In this paper, we propose a formal method that organizes a set of class interfaces into a lattice structure called Galois Lattice [10]. Such a lattice has several advantages including: 1) embodying protocol conformance, 2) supporting an incremental up...

The representation formalism as well as the representation language is of great importance for the success of machine learning. The representation formalism should be expressive, efficient, useful, and applicable. First-order logic needs to be restricted in order to be efficient for inductive and deductive reasoning. In the field of knowledge representation term subsumption formalisms have been developed which are efficient and expressive. In this paper, a learning algorithm, KLUSTER, is described which represents concept definitions in this formalism. KLUSTER enhances the representation language if this is necessary for the discrimination of concepts. Hence, KLUSTER is a constructive induction program. KLUSTER builds the most specific generalization and a most general discrimination in polynomial time. It embeds these concept learning problems into the overall task of learning a hierarchy of concepts.

There is a subtle risk of ambiguity in the choice between concepts and roles forced by current KL-ONE-like languages, since many roles may be concepts as well. In this paper we explore the ontological foundations of the role/concept relationship, and analyze its implications on the practice of knowledge engineering. We criticize the current interpretation of KL-ONE roles as arbitrary relations, which vanishes their original meaning and makes them identical to slots. We suggest to call attributes those concepts which actually act as conceptual components, and propose a formal semantics which binds these concepts to their corresponding relations.

Corporate databases increasingly are being viewed as potentially rich sources of new and valuable knowledge. Various approaches to"discovering" or "mining " such knowledge have been proposed. Here we identify an important and previously ignored discovery task, which we call data archaeology. Data archaeology is a skilled human task, in which the knowledge sought depends on the goals of the analyst, cannot be specified in advance, and emerges only through an iterative process of data segmentation and analysis. We describe a system that supports the data archaeologist with a natural, objectoriented representation of an application domain, a powerful query language and database translation routines, and an easy-to-use and flexible user interface that supports interactive exploration. A formal knowledge representation system provides the core technology that facilitates database integration, querying, and the reuse of queries and query results. Keywords: data archaeology, knowledge discov...

Due to the tremendously increasing popularity of the World-Wide Web, hypermedia is going to be the leading online information medium for some years to come and will most likely become the standard gateway for citizens to the "information highway". Already today, visitors of web sites are generally heterogeneous and have different needs, and this is likely to increase in the future. The aim of the AVANTI project is to cater hypermedia information to these individual needs by adapting the content and the presentation of web pages to each individual user. The special needs of elderly and disabled users are also partly considered. A model of the characteristics of user groups, individual users and usage environments, and a domain model are exploited in the adaptation process. One aim of this research is to verify that adaptation and user modeling techniques that were hitherto mostly used for catering interactive software systems to able-bodied users also prove useful for adaptation to users with special needs. Another original aspect is the development of a network-wide user modeling server that can concurrently accommodate the user modeling needs of several applications and several instances of an application within a distributed computing environment.

this paper, as well as utilizing such new and promising resources as on-line dictionaries. Recent work on machine-readable dictionaries offers new and interesting possibilities both for the computerassisted lexicology (see Walker 1984) and for construct- ing lexical databases derived from the definitions in machine-readable dictionaries and utilized in NLP along with other fields (see Amsler 1982, 1984a; Walker, Amsler 1986, Calzolari 1984a,b). The premises and goals of these efforts are fully compatible with our belief, first, that no AI system is ready to make the kind of decisions that lexicon building requires and, second, that 'simply having an online version of an encyclopedia [or a dictionary] would be of little use, as there is practically nothing that current AI could draw from the raw text. Rather, we must carefully re-represent the encyclopedia's knowledge -- by hand -- into some more structured form' (Lenat et al. 1986:75). Such re-representation would be necessary for Amsler's (1984a:458) 'lexical knowledge base [which] is a repos- itory of computational information about concepts' and which contains information derived from machine-read- able dictionaries, the full text of reference books, the results of statistical analysis of text usages, and data manually obtained from human world knowledge.' This paper deals primarily with the last item on Amsler's agenda. It is based on the following approach to the problem of lexicon building. The work is done by humans assisted by an interactive aid which enhances productivity and ensures uniformity. It is important to recognize that lexicon building in NLP involves the acquisition of not one entity but rather of three interre- lated but distinct lexicons, namely a) the world concept lexicon which structures our kno...

We describe a knowledge representation and inference formalism, based on an intensional propositional semantic network, in which variables are structured terms consisting of quantifier, type, and other information. This has three important consequences for natural language processing. First, this leads to an extended, more "natural" formalism whose use and representations are consistent with the use of variables in natural language in two ways: the structure of representations mirrors the structure of the language and allows re-use phenomena such as pronouns and ellipsis. Second, the formalism allows the specification of description subsumption as a partial ordering on related concepts (variable nodes in a semantic network) that relates more general concepts to more specific instances of that concept, as is done in language. Finally, this structured variable representation simplifies the resolution of some representational difficulties with certain classes of natural language sentences...

organisation ontology for the TOVE enterprise model. The ontology puts forward a number of conceptualizations for modeling organisations: agents, roles, positions, goals, communication, authority, commitment. Its primary focus has been in linking structure and behaviour through the concept of empowerment. Empowerment is the right of an organisation agent to perform status changing actions. This linkage is critical to the unification of enterprise models and their executability.