R. Agrawal and H. Jagadish. Algorithms for searching massive graphs. IEEE Transact. Knowledge and Data Eng., 6:225--238, 1994.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....segment when computing a path from event v to the station w it may be ignored. Another interesting approach outlined in [14] is to perform a graph reduc45 tion [32] on the train graph. The technique is common in transport routing applications and is motivated by work on searching massive graphs [1]. Certain stations transit hubs are deemed more important that others in transit networks based on their centrality in the transport network. Intuitively, these are the stations at which transfers are most likely to occur. Events in the train graph that occur at stations in the set of transit ....

Rakesh Agrawal and H. V. Jagadish. Algorithms for searching massive graphs. TKDE, 6(2):225-238, 1994.

....pages by the connectivity relationship. Ideally, the clustering maximizes WCRR. In particular, we address the following two issues. First, the static graph partitioning approach is not efficient when the entire network can not fit into main memory. In general, road maps are really large databases [16, 1], and thus may not fit inside main memory. Secondly, maintaining higher CRR in the face of Insert( and Delete( operations, without complete reorganization, is a critical problem. To solve the above two issues, we propose dynamic reclustering strategies to handle dynamic updating effects. ....

R. Agrawal and H.V. Jagadish. "Algorithms for Searching massive Graphs". IEEE Trans. on Knowledge and Data Engineering, 6(2), April 1994.

....[6, 7, 13, 25] has only focused on partitioning static graphs without considering dynamic updates. We address the following two issues. First, the static graph partitioning approach is not efficient when the entire network cannot fit into main memory. In general, road maps are very large databases [3, 26], and thus may not fit inside main memory. Second, maintaining a high WCRR in the face of Insert( and Delete( operations, without complete reorganization, is a critical problem. To solve the above two issues, we propose dynamic reclustering strategies to handle dynamic updating effects. ....

R. Agrawal and H.V. Jagadish. "Algorithms for Searching Massive Graphs". IEEE Trans. on Knowledge and Data Engineering, 6(2), April 1994.

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R. Agrawal and H. Jagadish. Algorithms for searching massive graphs. IEEE Transact. Knowledge and Data Eng., 6:225--238, 1994.

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