Managing and Mining Graph Data part 55 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. . | 530 MANAGING AND MINING GRAPH DATA is collapsed to a single nock scli - loops implicitly represent recursion. Besides that recursion has not been invcsligaled much in the context of call-graph reduction and in parlicular noi. as a starting point. for reductions in addition to iteralionSi The icason lor that is as we will see in the following that the reduction of recutsion is less obviour than reducing iterations and might finally result in riiv ramc gtaphs ar avilii a total reduction. Furthermore in computeintensive application progtamrnvrv Irii pnenti replace recursions with itera-tionSp as this a -riidu cosily method calls. Nvvcrthclcss. we have investigated recuosion-bated ocductior of ciII graphs to v certain extent and present some tipptoachcs in live lollorvtnVi Two typet of sccursion can be distinguished Direct recursion. When a method calls itself dltcclly. such a method call is called a direct recursion. An example is given in Figure where Method b calls ilaself. Figure UJb preventt a possible reduction represented with a self-loop al Node b. In Fivure 17i7b take weights as in RSUbbes represent hotit frequencier t S iterations and the depth of direct recuision. Indirect recursion. It may happen that some method calls another method which ln turn caHs first one again. This leads to a chain of method callsv as in ihe cvamplc m Figure where b calls c which agitin calls b etc. Such chains can he ol arhiiiaiy langth. Obviously such indirect recurs ions Gin he reduced as shown in Figures d . This cads to the existence of loops. at e b c d Figure . Examples for reduction based on recursion. Bath ryoes of rccussion ara chailenging when it comes to reduction. Figures rl i 1 one way ot reducing dirert recursions. While the subsequent rvltcxive calls of a are merged mto a singte node with a weighted setfiioop b c and d become siblmgs. As tv iii total veductions this leads to nerv ttruclurcs which do noi ocean hi the .
