{"title":"Twig query processing over graph-structured XML data","authors":"Zografoula Vagena, Mirella M. Moro, V. Tsotras","doi":"10.1145/1017074.1017087","DOIUrl":null,"url":null,"abstract":"XML and semi-structured data is usually modeled using graph structures. Structural summaries, which have been proposed to speedup XML query processing have graph forms as well. The existent approaches for evaluating queries over tree structured data (i.e. data whose underlying structure is a tree) are not directly applicable when the data is modeled as a random graph. Moreover, they cannot be applied when structural summaries are employed and, to the best of our knowledge, no analogous techniques have been reported for this case either. As a result, the potential of structural summaries is not fully exploited.In this paper, we investigate query evaluation techniques applicable to graph-structured data. We propose efficient algorithms for the case of directed acyclic graphs, which appear in many real world situations. We then tailor our approaches to handle other directed graphs as well. Our experimental evaluation reveals the advantages of our solutions over existing methods for graph-structured data.","PeriodicalId":93360,"journal":{"name":"Proceedings of the 5th International Workshop on Exploratory Search in Databases and the Web. International Workshop on Exploratory Search in Databases and the Web (5th : 2018 : Houston, Tex.)","volume":"25 1","pages":"43-48"},"PeriodicalIF":0.0000,"publicationDate":"2004-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"36","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 5th International Workshop on Exploratory Search in Databases and the Web. International Workshop on Exploratory Search in Databases and the Web (5th : 2018 : Houston, Tex.)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1017074.1017087","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 36
Abstract
XML and semi-structured data is usually modeled using graph structures. Structural summaries, which have been proposed to speedup XML query processing have graph forms as well. The existent approaches for evaluating queries over tree structured data (i.e. data whose underlying structure is a tree) are not directly applicable when the data is modeled as a random graph. Moreover, they cannot be applied when structural summaries are employed and, to the best of our knowledge, no analogous techniques have been reported for this case either. As a result, the potential of structural summaries is not fully exploited.In this paper, we investigate query evaluation techniques applicable to graph-structured data. We propose efficient algorithms for the case of directed acyclic graphs, which appear in many real world situations. We then tailor our approaches to handle other directed graphs as well. Our experimental evaluation reveals the advantages of our solutions over existing methods for graph-structured data.