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Managing and Mining Graph Data part 21

Managing and Mining Graph Data part 21 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. . | 1882 MANAGING AND MINING GRAPH DATA different links the parcnt-chitd -inks document-internal links and reference links cross-document links where the cross-document links are supported by vaiuc matching us-ng IDJDREF in XML. XLink -XML klnking Language 19 and XPointer -XML Pointe- Language 2tl provide more facilities for Liters So manage thei- complex data ns grafhs rnd integrate data effectively. The dominance of graphs in real-worid applications demands new graph data mana-eir-cnt so i.hat users can access graph data effectively and efficiently. Graph reachability tins rlmply reachal-ililyt queries to test whether there is a path from a node v to another node u in a large directed araph. have being studied l 14- 17 28-30 23 13 264 310 9 t4 5t 26 25 10 and are deemed to be a very basic i-sspe of graph queries loe many applications. Consider a semantic network that reprecents paoptc as nodes in the graph and relationships among people as edges in die grapht There are needs to understand whether -wo peoala arc rel tc l fo security reasons 2 i On biological networks where nodes thirst eiffier moloculcSi oi reactions- of physical interactions of living cells aed edges are mteractions among them. there i an important question to find all genes whoae exptest-ont cre directly oi mdtcectly influenced by a given molecule 133 All thoic quettions can i-e maaped into reachability queries. The nefds of such a r acirchHiti query can he also found in XML when two -ypef til links documcnt-ietcreai Stnkr and crose-document links are treated -he same. Recently 8- 12 35 nSudied gsaph matching problem on large graph datat where nodes in a match sine connic-ed by reachability relationshins. Rctichabili l.y queries arc co common that. fast processing is mandatory. Reachability Queries Let G V E Itc a large dircctcsi graph that has n nod e and m edges. A reac afeffi iy queries is dtnoted as u v where u and v are two nodes in G. Here u v returns true if and only if ffiere is a di-tccied