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Mixed heuristic search for sketch prediction on chemical structure drawing
| Content Provider | ACM Digital Library |
|---|---|
| Author | Hu, Hao Kang, Bo LaViola, Joseph J. |
| 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. |
| Starting Page | 27 |
| Ending Page | 34 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781450330183 |
| DOI | 10.1145/2630407.2630408 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2014-08-08 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Chemical structure sketch prediction Graph search Heuristics Hamiltonian path |
| Content Type | Text |
| Resource Type | Article |
