Mixed heuristic search for sketch prediction on chemical structure drawing
Bo Kang, Hao Hu, Joseph J. LaViola, Jr.
Proceedings of the 4th Joint Symposium on Computational Aesthetics, Non-Photorealistic Animation and Rendering, and Sketch-Based Interfaces and Modeling, 2014, pp. 27--34.
Abstract: Sketching is a natural way to input chemical structures that can be used to query information from a large chemical structure database. Based on a user's incomplete sketch of a chemical structure, sketch prediction becomes a challenging problem not only due to arbitrary drawings orders among users but also similarities among chemical structure layouts. In this paper, we present a graph-based approach to handle the sketch prediction problem. We use multisets as the data representation of hand-drawn chemical structures and create an undirected graph to handle data in all multisets. This approach transforms the sketch prediction problem into a search problem to find a hamiltonian path in the corresponding sub-graph with polynomial time complexity. We introduce mixed heuristics to guide the search procedure. Through an initial experiment on a hand-drawn chemical structure dataset, we demonstrate that in comparison with a baseline method, the proposed approach improves the prediction accuracy and efficiently predicts chemical structures from only partially sketched drawings.
@inproceedings{10.1145-2630407.2630408,
author = {Bo Kang and Hao Hu and Joseph J. LaViola, Jr.},
title = {Mixed heuristic search for sketch prediction on chemical structure drawing},
booktitle = {Proceedings of the 4th Joint Symposium on Computational Aesthetics, Non-Photorealistic Animation and Rendering, and Sketch-Based Interfaces and Modeling},
pages = {27--34},
year = {2014},
}
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