{"title":"Mixed heuristic search for sketch prediction on chemical structure drawing","authors":"Bo Kang, Hao Hu, J. Laviola","doi":"10.1145/2630407.2630408","DOIUrl":null,"url":null,"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.","PeriodicalId":289409,"journal":{"name":"International Symposium on Sketch-Based Interfaces and Modeling","volume":"344 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Symposium on Sketch-Based Interfaces and Modeling","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2630407.2630408","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
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.