Computational geometry: an introduction
Computational geometry: an introduction
Temporal databases: theory, design, and implementation
Temporal databases: theory, design, and implementation
Indexing for data models with constraints and classes
Journal of Computer and System Sciences
LH*—a scalable, distributed data structure
ACM Transactions on Database Systems (TODS)
A data structure for lattice representation
Ordal'94 Selected papers from the conference on Orders, algorithms and applications
Graph-theoretic methods in database theory
PODS '90 Proceedings of the ninth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Balanced Distributed Search Trees Do Not Exist
WADS '95 Proceedings of the 4th International Workshop on Algorithms and Data Structures
Sorting and Searching on the Word RAM
STACS '98 Proceedings of the 15th Annual Symposium on Theoretical Aspects of Computer Science
Compact Implicit Representation of Graphs
WG '98 Proceedings of the 24th International Workshop on Graph-Theoretic Concepts in Computer Science
Storing a sparse table with O(1) worst case access time
SFCS '82 Proceedings of the 23rd Annual Symposium on Foundations of Computer Science
A Reference Architecture for the Certification of E-Services in a Digital Government Infrastructure
Distributed and Parallel Databases
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We introduce an innovative decomposition technique which reduces a multi-dimensional searching problem to a sequence of one-dimensional problems, each one easily manageable in optimal time脳space complexity using traditional searching strategies. The reduction has no additional storage requirement and the time complexity to reconstruct the result of the original multi-dimensional query is linear in the dimension.More precisely, we showhowto preprocess a set of S 驴 INd of multi-dimensional objects into a data structure requiring O(mlog n) space, where m = |S| and n is the maximum number of different values for each coordinate. The obtained data structure is implicit, i.e. does not use pointers, and is able to answer the exact match query in 7(d - 1) steps. Additionally, the model of computation required for querying the data structure is very simple; the only arithmetic operation needed is the addition and no shift operation is used.The technique introduced, overcoming the multi-dimensional bottleneck, can be also applied to non traditional models of computation as external memory, distributed, and hierarchical environments. Additionally, we will show how the proposed technique permits the effective realizability of the well known perfect hashing techniques on real data.The algorithms for building the data structure are easy to implement and run in polynomial time.