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Computational Approaches to the Analysis of Human Creativity

  • Fabio Celli
Chapter
Part of the Lecture Notes in Morphogenesis book series (LECTMORPH)

Abstract

In this paper we address the issue of creativity and style computation from a natural language processing perspective. We introduce a computational framework for creativity analysis with two approaches, one agnostic, based on clustering, and one knowlegde-based, that exploits supervised learning and feature selection. While the agnostic approach can reveal the uniqueness of authors in a meaningful context, the knowledge-based approach can be exploited to extract the culturally relevant features of works and to predict social acceptance. In both the approaches, it is required a great effort to define symbols to represent meaningful cues in creativity and style.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.University of TrentoTrentoItaly

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