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R. Agrawal, H.V. Jagadish, "Algorithms for Searching Massive Graphs," IEEE Transactions on Knowledge and Data Engineering, vol. 6, no. 2, pp. 225238, April, 1994.  
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@article{ 10.1109/69.277767, author = {R. Agrawal and H.V. Jagadish}, title = {Algorithms for Searching Massive Graphs}, journal ={IEEE Transactions on Knowledge and Data Engineering}, volume = {6}, number = {2}, issn = {10414347}, year = {1994}, pages = {225238}, doi = {http://doi.ieeecomputersociety.org/10.1109/69.277767}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
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TY  JOUR JO  IEEE Transactions on Knowledge and Data Engineering TI  Algorithms for Searching Massive Graphs IS  2 SN  10414347 SP225 EP238 EPD  225238 A1  R. Agrawal, A1  H.V. Jagadish, PY  1994 KW  graph theory; search problems; deductive databases; data structures; query processing; very large databases; approximation theory; database theory; massive graphs; simulation; disk storage; dataintensive expert system; path problems; deductive database systems; data structuring technique; branch and bound search algorithm; search space pruning; successive approximations; path queries; query processing; shortest distance VL  6 JA  IEEE Transactions on Knowledge and Data Engineering ER   
Given a large graph, stored on disk, there is often a need to perform a search over this graph. Such a need could arise, for example, in the search component of a dataintensive expert system or to solve path problems in deductive database systems. In this paper, we present a novel data structuring technique and show how a branchandbound search algorithm can use this data structuring to prune the search space. Simulation results confirm that, using these techniques, a search can be expedited significantly without incurring a large storage penalty. As a side benefit, it is possible to organize the search to obtain successive approximations to the desired solution with considerable reduction in the total search.
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