Data-Driven Creativity Enhancement Through Word Association

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Creator: 

Hillen, Connor Leo Douglas

Date: 

2019

Abstract: 

Writing creative stories from a blank page is a challenging task, particularly in the modern game industry where dozens of writers can contribute to the stories and settings of a constantly evolving artificial world. We introduce a system which recommends interesting, evocative, and thematically coherent words to help creators write thematically connected stories. We combine principles from human creativity enhancement and computational creativity to build a creative assistant based on word association research. We show that careful corpus selection, filtering based on emotional sentiment, and promoting remote associations through paragraph scale segmentation can produce recommendations that promote creative goals better than alternative word association algorithms according to our creative word indicators.

Subject: 

Information Science

Language: 

English

Publisher: 

Carleton University

Thesis Degree Name: 

Master of Computer Science: 
M.C.S.

Thesis Degree Level: 

Master's

Thesis Degree Discipline: 

Computer Science

Parent Collection: 

Theses and Dissertations

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