Graph grammar induction on structural data for visual programming

Keven Ates; Jacek Kukluk; Lawrence Holder; Diane Cook; Kang Zhang

doi:10.1109/ICTAI.2006.61

Graph grammar induction on structural data for visual programming

Keven Ates^*, Jacek Kukluk, Lawrence Holder, Diane Cook, Kang Zhang

^*Corresponding author for this work

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

20 Citations (Scopus)

Abstract

Computer programs that can be expressed in two or more dimensions are typically called visual programs. The underlying theories of visual programming languages involve graph grammars. As graph grammars are usually constructed manually, construction can be a time-consuming process that demands technical knowledge. Therefore, a technique for automatically constructing graph grammars - at least in part - is desirable. An induction method is given to infer node replacement graph grammars. The method operates on labeled graphs of broad applicability. It is evaluated by its performance on inferring graph grammars from various structural representations. The correctness of an inferred grammar is verified by parsing graphs not present in the training set.

Original language	English
Title of host publication	Procedings - 18th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2006
Pages	232-239
Number of pages	8
DOIs	https://doi.org/10.1109/ICTAI.2006.61
Publication status	Published - 2006
Externally published	Yes
Event	18th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2006 - Arlington, VA, United States Duration: 13 Oct 2006 → 15 Oct 2006

Publication series

Name	Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI
ISSN (Print)	1082-3409

Conference

Conference	18th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2006
Country/Territory	United States
City	Arlington, VA
Period	13/10/06 → 15/10/06

Access to Document

10.1109/ICTAI.2006.61

Cite this

Ates, K., Kukluk, J., Holder, L., Cook, D., & Zhang, K. (2006). Graph grammar induction on structural data for visual programming. In Procedings - 18th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2006 (pp. 232-239). Article 4031903 (Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI). https://doi.org/10.1109/ICTAI.2006.61

@inproceedings{15f0fb8af0bc436680d7aea5c2c7e8dc,

title = "Graph grammar induction on structural data for visual programming",

abstract = "Computer programs that can be expressed in two or more dimensions are typically called visual programs. The underlying theories of visual programming languages involve graph grammars. As graph grammars are usually constructed manually, construction can be a time-consuming process that demands technical knowledge. Therefore, a technique for automatically constructing graph grammars - at least in part - is desirable. An induction method is given to infer node replacement graph grammars. The method operates on labeled graphs of broad applicability. It is evaluated by its performance on inferring graph grammars from various structural representations. The correctness of an inferred grammar is verified by parsing graphs not present in the training set.",

author = "Keven Ates and Jacek Kukluk and Lawrence Holder and Diane Cook and Kang Zhang",

year = "2006",

doi = "10.1109/ICTAI.2006.61",

language = "English",

isbn = "0769527280",

series = "Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI",

pages = "232--239",

booktitle = "Procedings - 18th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2006",

note = "18th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2006 ; Conference date: 13-10-2006 Through 15-10-2006",

}

Ates, K, Kukluk, J, Holder, L, Cook, D & Zhang, K 2006, Graph grammar induction on structural data for visual programming. in Procedings - 18th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2006., 4031903, Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI, pp. 232-239, 18th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2006, Arlington, VA, United States, 13/10/06. https://doi.org/10.1109/ICTAI.2006.61

Graph grammar induction on structural data for visual programming. / Ates, Keven; Kukluk, Jacek; Holder, Lawrence et al.
Procedings - 18th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2006. 2006. p. 232-239 4031903 (Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI).

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

TY - GEN

T1 - Graph grammar induction on structural data for visual programming

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AU - Kukluk, Jacek

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AU - Cook, Diane

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AB - Computer programs that can be expressed in two or more dimensions are typically called visual programs. The underlying theories of visual programming languages involve graph grammars. As graph grammars are usually constructed manually, construction can be a time-consuming process that demands technical knowledge. Therefore, a technique for automatically constructing graph grammars - at least in part - is desirable. An induction method is given to infer node replacement graph grammars. The method operates on labeled graphs of broad applicability. It is evaluated by its performance on inferring graph grammars from various structural representations. The correctness of an inferred grammar is verified by parsing graphs not present in the training set.

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DO - 10.1109/ICTAI.2006.61

M3 - Conference Paper published in a book

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SN - 9780769527284

T3 - Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI

SP - 232

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BT - Procedings - 18th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2006

T2 - 18th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2006

Y2 - 13 October 2006 through 15 October 2006

ER -

Graph grammar induction on structural data for visual programming

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