Results 1  10
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162
Index Structures for Path Expressions
, 1997
"... In recent years there has been an increased interest in managing data which does not conform to traditional data models, like the relational or object oriented model. The reasons for this nonconformance are diverse. One one hand, data may not conform to such models at the physical level: it may be ..."
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Cited by 333 (7 self)
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In recent years there has been an increased interest in managing data which does not conform to traditional data models, like the relational or object oriented model. The reasons for this nonconformance are diverse. One one hand, data may not conform to such models at the physical level: it may be stored in data exchange formats, fetched from the Internet, or stored as structured les. One the other hand, it may not conform at the logical level: data may have missing attributes, some attributes may be of di erent types in di erent data items, there may be heterogeneous collections, or the data may be simply specified by a schema which is too complex or changes too often to be described easily as a traditional schema. The term semistructured data has been used to refer to such data. The data model proposed for this kind of data consists of an edgelabeled graph, in which nodes correspond to objects and edges to attributes or values. Figure 1 illustrates a semistructured database providing information about a city. Relational databases are traditionally queried with associative queries, retrieving tuples based on the value of some attributes. To answer such queries efciently, database management systems support indexes for translating attribute values into tuple ids (e.g. Btrees or hash tables). In objectoriented databases, path queries replace the simpler associative queries. Several data structures have been proposed for answering path queries e ciently: e.g., access support relations 14] and path indexes 4]. In the case of semistructured data, queries are even more complex, because they may contain generalized path expressions 1, 7, 8, 16]. The additional exibility is needed in order to traverse data whose structure is irregular, or partially unknown to the user.
Fast Approximation Algorithms for Multicommodity Flow Problems
 JOURNAL OF COMPUTER AND SYSTEM SCIENCES
, 1991
"... All previously known algorithms for solving the multicommodity flow problem with capacities are based on linear programming. The best of these algorithms [15] uses a fast matrix multiplication algorithm and takes O(k 3:5 n 3 m :5 log(nDU )) time for the multicommodity flow problem with inte ..."
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Cited by 191 (21 self)
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All previously known algorithms for solving the multicommodity flow problem with capacities are based on linear programming. The best of these algorithms [15] uses a fast matrix multiplication algorithm and takes O(k 3:5 n 3 m :5 log(nDU )) time for the multicommodity flow problem with integer demands and at least O(k 2:5 n 2 m :5 log(nffl \Gamma1 DU )) time to find an approximate solution, where k is the number of commodities, n and m denote the number of nodes and edges in the network, D is the largest demand, and U is the largest edge capacity. Substantially more time is needed to find an exact solution. As a consequence, even multicommodity flow problems with just a few commodities are believed to be much harder than singlecommodity maximumflow or minimumcost flow problems. In this paper, we describe the first polynomialtime combinatorial algorithms for approximately solving the multicommodity flow problem. The running time of our randomized algorithm i...
Shortest Paths Algorithms: Theory And Experimental Evaluation
 Mathematical Programming
, 1993
"... . We conduct an extensive computational study of shortest paths algorithms, including some very recent algorithms. We also suggest new algorithms motivated by the experimental results and prove interesting theoretical results suggested by the experimental data. Our computational study is based on se ..."
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Cited by 188 (15 self)
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. We conduct an extensive computational study of shortest paths algorithms, including some very recent algorithms. We also suggest new algorithms motivated by the experimental results and prove interesting theoretical results suggested by the experimental data. Our computational study is based on several natural problem classes which identify strengths and weaknesses of various algorithms. These problem classes and algorithm implementations form an environment for testing the performance of shortest paths algorithms. The interaction between the experimental evaluation of algorithm behavior and the theoretical analysis of algorithm performance plays an important role in our research. Andrew V. Goldberg was supported in part by ONR Young Investigator Award N0001491J1855, NSF Presidential Young Investigator Grant CCR8858097 with matching funds from AT&T, DEC, and 3M, and a grant from Powell Foundation. This work was done while Boris V. Cherkassky was visiting Stanford University Compu...
Optimizing regular path expressions using graph schemas,
 Proceedings of the Fourteenth International Conference on Data Engineering,
, 1998
"... ..."
On the Editing Distance between Undirected Acyclic Graphs
, 1995
"... We consider the problem of comparing CUAL graphs (Connected, Undirected, Acyclic graphs with nodes being Labeled). This problem is motivated by the study of information retrieval for biochemical and molecular databases. Suppose we define the distance between two CUAL graphs G1 and G2 to be the weig ..."
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Cited by 88 (7 self)
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We consider the problem of comparing CUAL graphs (Connected, Undirected, Acyclic graphs with nodes being Labeled). This problem is motivated by the study of information retrieval for biochemical and molecular databases. Suppose we define the distance between two CUAL graphs G1 and G2 to be the weighted number of edit operations (insert node, delete node and relabel node) to transform G1 to G2. By reduction from exact cover by 3sets, one can show that finding the distance between two CUAL graphs is NPcomplete. In view of the hardness of the problem, we propose a constrained distance metric, called the degree2 distance, by requiring that any node to be inserted (deleted) have no more than 2 neighbors. With this metric, we present an efficient algorithm to solve the problem. The algorithm runs in time O(N_1 N_2 D&sup2;) for general weighting edit operations and in time O(N_1 N_2 D &radic;D log D) for integral weighting edit operations, where N_i, i = 1, 2, is the number of nodes in G_i, D = min{d_1, d_2} and d_i is the maximum degree of G_i.
Planar Graphs, Negative Weight Edges, Shortest Paths, and Near Linear Time
 In Proc. 42nd IEEE Annual Symposium on Foundations of Computer Science
, 2001
"... for finding shortest paths in a planar graph with real weights. ..."
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Cited by 69 (0 self)
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for finding shortest paths in a planar graph with real weights.
Exact and Approximate Distances in Graphs  a survey
 In ESA
, 2001
"... We survey recent and not so recent results related to the computation of exact and approximate distances, and corresponding shortest, or almost shortest, paths in graphs. We consider many different settings and models and try to identify some remaining open problems. ..."
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Cited by 68 (0 self)
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We survey recent and not so recent results related to the computation of exact and approximate distances, and corresponding shortest, or almost shortest, paths in graphs. We consider many different settings and models and try to identify some remaining open problems.
Greedy matchings.
, 2003
"... Abstract Suppose that each member of a set A of applicants ranks a subset of a set P of posts in an order of preference, possibly involving ties. A matching is a set of (applicant, post) pairs such that each applicant and each post appears in at most one pair. A rankmaximal matching is one in whic ..."
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Cited by 55 (16 self)
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Abstract Suppose that each member of a set A of applicants ranks a subset of a set P of posts in an order of preference, possibly involving ties. A matching is a set of (applicant, post) pairs such that each applicant and each post appears in at most one pair. A rankmaximal matching is one in which the maximum possible number of applicants are matched to their first choice post, and subject to that condition, the maximum possible number are matched to their second choice post, and so on. This is a relevant concept in any practical matching situation and it was first studied by Irving We give an algorithm to compute a rankmaximal matching with running time O(min(n +C,C √ n)m), where C is the maximal rank of an edge used in a rankmaximal matching, n is the number of applicants and posts and m is the total size of the preference lists.