{"title":"晶体结构中相似多面体簇的搜索和排序","authors":"Hans-Joachim Klein, Christian Mennerich","doi":"10.1109/ADVCOMP.2008.34","DOIUrl":null,"url":null,"abstract":"A graph-based method is described for searching and ranking clusters of polyhedra in large crystallographic databases. First, embeddings of topologically equivalent substructures are determined for a given target cluster based upon a graph representation of polyhedral networks. Then, an algorithm for solving the problem of absolute orientation is applied in order to rank topologically equivalent clusters according to their geometric similarity.","PeriodicalId":269090,"journal":{"name":"2008 The Second International Conference on Advanced Engineering Computing and Applications in Sciences","volume":"122 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Searching and Ranking Similar Clusters of Polyhedra in Crystal Structures\",\"authors\":\"Hans-Joachim Klein, Christian Mennerich\",\"doi\":\"10.1109/ADVCOMP.2008.34\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A graph-based method is described for searching and ranking clusters of polyhedra in large crystallographic databases. First, embeddings of topologically equivalent substructures are determined for a given target cluster based upon a graph representation of polyhedral networks. Then, an algorithm for solving the problem of absolute orientation is applied in order to rank topologically equivalent clusters according to their geometric similarity.\",\"PeriodicalId\":269090,\"journal\":{\"name\":\"2008 The Second International Conference on Advanced Engineering Computing and Applications in Sciences\",\"volume\":\"122 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-09-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 The Second International Conference on Advanced Engineering Computing and Applications in Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ADVCOMP.2008.34\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 The Second International Conference on Advanced Engineering Computing and Applications in Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ADVCOMP.2008.34","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Searching and Ranking Similar Clusters of Polyhedra in Crystal Structures
A graph-based method is described for searching and ranking clusters of polyhedra in large crystallographic databases. First, embeddings of topologically equivalent substructures are determined for a given target cluster based upon a graph representation of polyhedral networks. Then, an algorithm for solving the problem of absolute orientation is applied in order to rank topologically equivalent clusters according to their geometric similarity.
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