|Bibliography||Falkenthal, Michael; Barzen, Johanna; Breitenbücher, Uwe; Brügmann, Sascha; Joos, Daniel; Leymann, Frank; Wurster, Michael: Pattern Research in the Digital Humanities: How Data Mining Techniques Support the Identification of Costume Patterns. |
In: Computer Science - Research and Development.
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology.
Springer, November 5, 2016.
Article in Journal.
|CR-Schema||H.2.8 (Database Applications)|
H.3.3 (Information Search and Retrieval)
Costumes are prominent in transporting a character's mood, a certain stereotype, or character trait in a film. The concept of patterns, applied to the domain of costumes in films, can help costume designers to improve their work by capturing knowledge and experience about proven solutions for recurring design problems. However, finding such Costume Patterns is a difficult and time-consuming task, because possibly hundreds of different costumes of a huge number of films have to be analyzed to find commonalities. In this paper, we present a Semi-Automated Costume Pattern Mining Method to discover indicators for Costume Patterns from a large data set of documented costumes using data mining and data warehouse techniques. We validate the presented approach by a prototypical implementation that builds upon the Apriori algorithm for mining association rules and standard data warehouse technologies.
|Department(s)||University of Stuttgart, Institute of Architecture of Application Systems|
|Entry date||November 7, 2016|