Expert and Corpus-Based Evaluation of a 3-Space Model of Conceptual Blending

This paper presents the 3-space model of conceptual blending that estimates the figurative similarity between Input spaces 1 and 2 using both their analogical similarity and the interconnecting Generic Space. We describe how our Dr Inventor model is being evaluated as a model of lexically based figurative similarity. We describe distinct but related evaluation tasks focused on 1) identifying novel and quality analogies between computer graphics publications 2) evaluation of machine generated translations of text documents 3) evaluation of documents in a plagiarism corpus. Our results show that Dr Inventor is capable of generating novel comparisons between publications but also appears to be a useful tool for evaluating machine translation systems and for detecting and assessing the level of plagiarism between documents. We also outline another more recent evaluation, using a corpus of patent applications

Can a Computationally Creative System Create Itself? Creative Artefacts and Creative Processes

This paper begins by briefly looking at two of the dominant perspectives on computational creativity; focusing on the creative artefacts and the creative processes respectively. We briefly describe two projects; one focused on (artistic) creative artefacts the other on a (scientific) creative process, to highlight some similarities and differences in approach. We then look at a 2- dimensional model of Learning Objectives that uses independent axes of knowledge and (cognitive) processes. This educational framework is then used to cast artefact and process perspectives into a common framework, opening up new possibilities for discussing and comparing creativity between them. Finally, arising from our model of creative processes, we propose a new and broad 4-level hierarchy of computational creativity, which asserts that the highest level of computational creativity involves processes whose creativity is comparable to that of the originating process itself

Embedding a Creativity Support Tool within Computer Graphics Research

We describe the Dr Inventor creativity support tool that aims to support and even enhance the creativity of active research scientists, by discovering un-noticed analogical similarities between publications. The tool combines text processing, lexical analysis and computational cognitive modelling to find comparisons with the greatest potential for a creative impact on the system users. A multi-year corpus of publications is used to drive the creativity of the system, with a central graph matching algorithm being adapted to identify the best analogy between any pair of papers. Dr Inventor has been developed for use by computer graphics researchers, with a particular focus on publications from the SIGGRAPH conference series and it uses this context in three main ways. Firstly, the pragmatic context of creativity support requires the identification of comparisons that are unlike pre-existing information. Secondly, the suggested inferences are assessed for quality within the context of a corpus of graphics publications. Finally, expert users from this discipline were asked to identify the qualities of greatest concern to them, which then guided the subsequent evaluation task