Modelling Creativity: Identifying Key Components through a Corpus-Based Approach

Creativity is a complex, multi-faceted concept encompassing a variety of related aspects, abilities, properties and behaviours. If we wish to study creativity scientifically, then a tractable and well-articulated model of creativity is required. Such a model would be of great value to researchers investigating the nature of creativity and in particular, those concerned with the evaluation of creative practice. This paper describes a unique approach to developing a suitable model of how creative behaviour emerges that is based on the words people use to describe the concept. Using techniques from the field of statistical natural language processing, we identify a collection of fourteen key components of creativity through an analysis of a corpus of academic papers on the topic. Words are identified which appear significantly often in connection with discussions of the concept. Using a measure of lexical similarity to help cluster these words, a number of distinct themes emerge, which collectively contribute to a comprehensive and multi-perspective model of creativity. The components provide an ontology of creativity: a set of building blocks which can be used to model creative practice in a variety of domains. The components have been employed in two case studies to evaluate the creativity of computational systems and have proven useful in articulating achievements of this work and directions for further research.

DATR Theories and DATR Models

Evans and Gazdar introduced DATR as a simple, non-monotonic language for representing natural language lexicons. Although a number of implementations of DATR exist, the full language has until now lacked an explicit, declarative semantics. This paper rectifies the situation by providing a mathematical semantics for DATR. We present a view of DATR as a language for defining certain kinds of partial functions by cases. The formal model provides a transparent treatment of DATR's notion of global context. It is shown that DATR's default mechanism can be accounted for by interpreting value descriptors as families of values indexed by paths.

A Tractable Extension of Linear Indexed Grammars

It has been shown that Linear Indexed Grammars can be processed in polynomial time by exploiting constraints which make possible the extensive use of structure-sharing. This paper describes a formalism that is more powerful than Linear Indexed Grammar, but which can also be processed in polynomial time using similar techniques. The formalism, which we refer to as Partially Linear PATR manipulates feature structures rather than stacks.