Evolutionary learning of graph layout constraints from examples

研究成果: Conference contribution

23 被引用数 (Scopus)

抄録

We propose a new evolutionary method of extracting user preferences from examples shown to an automatic graph layout system. Using stochastic methods such as simulated annealing and genetic algorithms, automatic layout systems can find a good layout using an evaluation function which can calculate how good a given layout is. However, the evaluation function is usually not known beforehand, and it might vary from user to user. In our system, users show the system several pairs of good and bad layout examples, and the system infers the evaluation function from the examples using genetic programming technique. After the evaluation function evolves to reflect the preferences of the user, it is used as a general evaluation function for laying out graphs. The same technique can be used for a wide range of adaptive user interface systems.

本文言語English
ホスト出版物のタイトルProceedings of the 7th Annual ACM Symposium on User Interface Software and Technology, UIST 1994
出版社Association for Computing Machinery, Inc
ページ103-108
ページ数6
ISBN(電子版)0897916573, 9780897916578
DOI
出版ステータスPublished - 1994 11 2
外部発表はい
イベント7th Annual ACM Symposium on User Interface Software and Technology, UIST 1994 - Marina del Rey, United States
継続期間: 1994 11 21994 11 4

出版物シリーズ

名前Proceedings of the 7th Annual ACM Symposium on User Interface Software and Technology, UIST 1994

Other

Other7th Annual ACM Symposium on User Interface Software and Technology, UIST 1994
国/地域United States
CityMarina del Rey
Period94/11/294/11/4

ASJC Scopus subject areas

  • 人間とコンピュータの相互作用
  • コンピュータ グラフィックスおよびコンピュータ支援設計
  • ソフトウェア

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