### Table 3 Performance of Shortest Path Search

"... In PAGE 2: ... This allows us to test if a general link classification model could be obtained to apply to unseen Websites. We build different versions of weighted directed graphs using each of the three types of classifiers and compare the performances of the algorithms on the different graphs Table3 and 4. As can be seen from the results, the SPS and DMST algorithms using weighted graph models outperform the simple BFS significantly.... ..."

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### Table 3 Shortest-path running times

"... In PAGE 7: ...1. Shortest-path algorithms We have collected the running times, from [12] in Table3 (the largest problem instances only). 13 Table 4 contains the ranking of the algorithms based on their running times.... ..."

### Table 3 Shortest-path running times

"... In PAGE 7: ...1. Shortest-path algorithms We have collected the running times, from [12] in Table3 (the largest problem instances only). Table 4 contains the ranking of the algorithms based on their running times.... ..."

### Table 1 Comple xity results on characterization of shortest-path IRSs

"... In PAGE 3: ... A summary of these and other results can be found in [9]. For general graphs, existing comple xity results for the weighted/unweighted models and various IRS variants are summarized in Table1 , where an entry for any of the single-path IRS or global compactness refers to both the strict and non-strict versions of the problem; an entry for the all-shortest-path IRS of edge compactness refers to both the linear and non-linear versions of the problem; NPC denotes an NP-complete problem. All the problems related to single-shortest-path IRS are known to be NP-complete.... ..."

### Table 2. Shortest Path Table

"... In PAGE 5: ... 3. Graph representation for function (6) Table2 summarizes the SP of this graph. NP, NN, SSP, and MNNAP are summarized in Table 3.... ..."

### Table 1. Number of elements, length of the shortest path and processing time for each graph by our algorithm

2000

"... In PAGE 4: ... It can be seen that the region in which a path exists gradually becomes narrower and finally con- verges to a poly line. Table1 shows the number of elements (vertices, edges) on Gi, the length of shortest path li and the sum of each pro- cessing time for STEP 1 - STEP 4. Our algorithm searches almost a constant number of edges (from 350 to 400 in this example) on each graph Gi, except for G0 in the first stage which has a large number of edges.... ..."

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### Table 1: Comparison between shortest paths through nodes in closed list and actual paths

2004

"... In PAGE 21: ... However, solving this problem optimally was feasible only for relatively small graph sizes. Table1 provides a comparison between PHA* and the shortest path that travels through all the closed nodes for various small sized graphs. The table indicates that our PHA* algorithm is quite e cient for small graphs.... ..."

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### Table 3: Parallel Shortest Path Algorithm

1997

"... In PAGE 4: ... Our parallel shortest path algorithm uses the SPMD model for which each processor solves the portion of the shortest path tree on its subnetwork for each source. The outline of the algorithm is given in Table3 . Each processor repeatedly solves for shortest paths for its assigned subnetwork.... ..."

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### Table 3: Parallel Shortest Path Algorithm

1997

"... In PAGE 4: ... Our parallel shortest path algorithm uses the SPMD model for which each processor solves the portion of the shortest path tree on its subnetwork for each source. The outline of the algorithm is given in Table3 . Each processor repeatedly solves for shortest paths for its assigned subnetwork.... ..."

Cited by 7