TAILIEUCHUNG - Managing and Mining Graph Data part 26

Managing and Mining Graph Data part 26 is a comprehensive survey book in graph data analytics. It contains extensive surveys on important graph topics such as graph languages, indexing, clustering, data generation, pattern mining, classification, keyword search, pattern matching, and privacy. It also studies a number of domain-specific scenarios such as stream mining, web graphs, social networks, chemical and biological data. The chapters are written by leading researchers, and provide a broad perspective of the area. This is the first comprehensive survey book in the emerging topic of graph data processing. . | Exact and Inexact Graph Matching Methodology and Applications 233 Query graphs are more general than common graphs in the sense that don t care symbol and variables may occur as the values of attributes on the nodes and edges. The purpose of the variables is to tlaline those attributes whose vaSurs ins la he returned as a n answer ta e query we will come back to this point. Sader . hi lisa. b an sxarnplc of e query graph with variables X. Y and does care symbols is given. According to this query we are partic-sitaHyn istcrcelcd San the subject X and tier date Y of an e-mail sent from Joha .Arnold eo dna Rangd. As ws do cot. caec about the size of the e-mail and wo do not ksorv the ccnail addresa of Ina Rengel two don t care symbols are used. Vasiabres may also occsn in a castcry because they may be used to express conrireinte on rritv or ssrvcr-sri attribute valuea. A constraint on a set of variables occurring Sn a query graph ns a conlition on ona or several variables that evaluates to true or false if we aesign st concrete attribute value to each variable. For iniiancc. the query in Figi b can ire aurmented by the constraint that the ermeia in question was sail hetwaen October 1 and October 3 formally 9 31 00 Y 10 4 00 . Ones query yeaph han been constructed by the user it is matched against a daiabasc graph. The process of matching a query graph to a database graph essentia y means ehot we want to find out svliethcr there exists a subgraph isomoephisits from rhe query to tian database graph. Obviously as the query graph i i-s r include cion a. cere symbols end variables we need a more general notion of sri 0 1 isomoephism than the one provided in Definition . Such a generahzed subgraeh Iromorchism bdwcsn a query and a database graph is ceicrrod to as a match . if a queey graph q marches a database graph G we cal 1 fine infective function f a match between q ami G. Note that. for given q and G ane a eiven ser of constraicts over the variables

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