A neural relaxation technique for chemical graph matching

M Turner; J Austin

A neural relaxation technique for chemical graph matching

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We develop a binary relaxation scheme for graph matching in chemical databases. The technique works by iteratively pruning the list of matching possibilities for individual atoms based upon contextual information. Its key features include delayed decisionmaking, robustness to noise, and fast and efficient neural implementation. We illustrate the utility of the technique by comparing it with probabilistic relaxation for a small database of 2D structures, and suggest that it may be applicable to matching in large databases of both 2D and 3D chemical graphs.

Original language	English
Title of host publication	FIFTH INTERNATIONAL CONFERENCE ON ARTIFICIAL NEURAL NETWORKS
Place of Publication	EDISON
Publisher	INST ELECTRICAL ENGINEERS INSPEC INC
Pages	187-192
Number of pages	6
ISBN (Print)	0-85296-690-3
Publication status	Published - 1997
Event	5th International Conference on Artificial Neural Networks - CAMBRIDGE Duration: 7 Jul 1997 → 9 Jul 1997

Conference

Conference	5th International Conference on Artificial Neural Networks
City	CAMBRIDGE
Period	7/07/97 → 9/07/97

Cite this

@inproceedings{60fd8fd7268e4134bb9fe70c27e43108,

title = "A neural relaxation technique for chemical graph matching",

abstract = "We develop a binary relaxation scheme for graph matching in chemical databases. The technique works by iteratively pruning the list of matching possibilities for individual atoms based upon contextual information. Its key features include delayed decisionmaking, robustness to noise, and fast and efficient neural implementation. We illustrate the utility of the technique by comparing it with probabilistic relaxation for a small database of 2D structures, and suggest that it may be applicable to matching in large databases of both 2D and 3D chemical graphs.",

author = "M Turner and J Austin",

year = "1997",

language = "English",

isbn = "0-85296-690-3",

pages = "187--192",

booktitle = "FIFTH INTERNATIONAL CONFERENCE ON ARTIFICIAL NEURAL NETWORKS",

publisher = "INST ELECTRICAL ENGINEERS INSPEC INC",

note = "5th International Conference on Artificial Neural Networks ; Conference date: 07-07-1997 Through 09-07-1997",

}

TY - GEN

T1 - A neural relaxation technique for chemical graph matching

AU - Turner, M

AU - Austin, J

PY - 1997

Y1 - 1997

N2 - We develop a binary relaxation scheme for graph matching in chemical databases. The technique works by iteratively pruning the list of matching possibilities for individual atoms based upon contextual information. Its key features include delayed decisionmaking, robustness to noise, and fast and efficient neural implementation. We illustrate the utility of the technique by comparing it with probabilistic relaxation for a small database of 2D structures, and suggest that it may be applicable to matching in large databases of both 2D and 3D chemical graphs.

AB - We develop a binary relaxation scheme for graph matching in chemical databases. The technique works by iteratively pruning the list of matching possibilities for individual atoms based upon contextual information. Its key features include delayed decisionmaking, robustness to noise, and fast and efficient neural implementation. We illustrate the utility of the technique by comparing it with probabilistic relaxation for a small database of 2D structures, and suggest that it may be applicable to matching in large databases of both 2D and 3D chemical graphs.

M3 - Conference contribution

SN - 0-85296-690-3

SP - 187

EP - 192

BT - FIFTH INTERNATIONAL CONFERENCE ON ARTIFICIAL NEURAL NETWORKS

PB - INST ELECTRICAL ENGINEERS INSPEC INC

CY - EDISON

T2 - 5th International Conference on Artificial Neural Networks

Y2 - 7 July 1997 through 9 July 1997

ER -