### Table 2: Results of some real graphs

2006

"... In PAGE 11: ...3 Real Graphs We also show results on some real graphs. The first four datasets in Table2 are from EcoCyc [13]. The last dataset is an XML document generated by the XMark benchmark [1].... ..."

Cited by 4

### Table 1: Performance of our algorithm on real graph for small number of changes.

"... In PAGE 11: ...dge added an edge from www.yahoo.com to www.cs.berkeley.edu. In these experiments, we used as our starting PageRank and our threshold while constructing the subgraph was 10?6. The results are described in Table1 . The rst column indicates the number of edges added.... ..."

### Table 4: Our results for real web graph.

"... In PAGE 12: ... We can see that each update requires far fewer computations than would be needed for the full 61 million pages and 259 million edges. At the end of all the updates, we have the results described in Table4 . If we let be the original PageRank, ~ be the new correct PageRank, and ^ the approximation given by our algorithm, we have that k ? ~ k = 0:12056 while k^ ? ~ k = 5:9552 10?5, meaning that we apos;ve eliminated 99.... ..."

### Table 2. Embedding public watermark to real life graph and randomized graph

2001

"... In PAGE 14: ...html) and the DIMACS on-line challenge graph. Table2 shows the number of vertices in each graph (vert. column), the opti- mal solutions (opt.... ..."

Cited by 1

### Table 1: Number of nodes and edges for real-world graphs.

"... In PAGE 5: ... (In all cases, the maximum connected component con- tained almost all if not all nodes.) The number of nodes and edges are listed in Table1 for real-world graphs and Table 2 for generated graphs. The graphs were drawn with the three methods de- scribed in Sect.... ..."

### Table 1. Graphs from real applications.

"... In PAGE 6: ...ased symbolic graph algorithms as proposed, e. g., by [6] or [17], can be more efficient than traditional graph algorithms. 4 Graphs from real applications The graphs which we have considered in our investigations are listed in Table1 . The second and third columns give the number of vertices and the number of edges of the graphs, respectively.... In PAGE 6: ... The second and third columns give the number of vertices and the number of edges of the graphs, respectively. Note that all of the graphs listed in Table1 are sparse, i. e.... In PAGE 6: ...he vertices, e. g., that presented in [5]. 4Because all the graphs of Table1 are undirected ones, every undirected edge was substituted by two directed edges during the construction of their OBDDs. Therefore, the numbers of edges of the graphs in this figure are the doubles of that in Table 1.... ..."

### Table 4: Coloring watermarked real-life graphs.

1999

"... In PAGE 15: ... Table4 reports the details. The #0Crst four columns shows the characteristic of the original graph and the known optimal solution; the next two are for technique #231, showing the number of edges #28information in bits#29 being embedded and the overhead; fol- lowed bytwo columns for technique #232, where the Size columns are the number of vertices in the selected MISes.... ..."

Cited by 3

### Table 4: Coloring watermarked real-life graphs.

1999

"... In PAGE 15: ... Table4 reports the details. The rst four columns shows the characteristic of the original graph and the known optimal solution;;the next t wo are for technique #1, showing the number of edges (information in bits) being embedded and the overhead;; fol- lowed bytwo columns for technique #2, where the Size columns are the number of vertices in the selected MISes.... ..."

Cited by 3

### Table 2. Results for real word graphs derivations runtime

1994

"... In PAGE 4: ...erent factors: 0.001,0.01,1 and 10. Table2 shows the average numberof syntactic derivations andthe average runtime, the first one only given for correctly recognized sentences. The number of correct sentences when using prosodic information is given as n1 + n2, n1 sentences being part of the 145 sentences which were correctly recognized without using prosodic information.... In PAGE 4: ... The number of correct sentences when using prosodic information is given as n1 + n2, n1 sentences being part of the 145 sentences which were correctly recognized without using prosodic information. (Note that runtimes of Table 1 and Table2 can not be compared becausedifferent machines were used). As can be seenthe num- ber of correctly recognized sentences decreases and the runtime increaseswhen the factorwith which the prosodic information is taken into account increases.... ..."

Cited by 12