Amitabha Bagchi, Adam L. Buchsbaum, Michael T. Goodrich's Algorithms and Computation: 13th International Symposium, PDF

By Amitabha Bagchi, Adam L. Buchsbaum, Michael T. Goodrich (auth.), Prosenjit Bose, Pat Morin (eds.)

ISBN-10: 3540001425

ISBN-13: 9783540001423

ISBN-10: 3540361367

ISBN-13: 9783540361367

This ebook constitutes the refereed court cases of the thirteenth Annual foreign Symposium on Algorithms and Computation, ISAAC 2002, held in Vancouver, BC, Canada in November 2002.

The fifty four revised complete papers provided including three invited contributions have been rigorously reviewed and chosen from as regards to a hundred and sixty submissions. The papers hide all correct issues in algorithmics and computation, particularly computational geometry, algorithms and information buildings, approximation algorithms, randomized algorithms, graph drawing and graph algorithms, combinatorial optimization, computational biology, computational finance, cryptography, and parallel and distributedd algorithms.

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Extra info for Algorithms and Computation: 13th International Symposium, ISAAC 2002 Vancouver, BC, Canada, November 21–23, 2002 Proceedings

Sample text

However, they do not meet our definition of a standard binary search tree structure, because there are additional pointers that the trees must be augmented with. However, it was shown that splay trees have the dynamic finger property [3,2]. The dynamic finger property implies the static finger property. Neither the dynamic finger property nor the working set property imply each other, and these are known to be the two best analyses of splay trees, and search trees in general. We now leave the proven properties of binary search trees and continue on to conjectured properties.

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The score Space-Efficient Data Structures for Flexible Text Retrieval Systems 21 of a document for a set of given keywords p is defined as p tf (p, d) · idf (p), and ranks of documents are defined in decreasing order of the score. The inverse document frequency is used to decrease the weight of keywords which appear in many documents because such keywords are not important. The tf and idf scores are stored in the inverted file in addition to document id’s. For each keyword p appearing in a set of documents, the idf (p) score and pairs (d, tf (p, d)) for all documents d that contain p are stored.

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Algorithms and Computation: 13th International Symposium, ISAAC 2002 Vancouver, BC, Canada, November 21–23, 2002 Proceedings by Amitabha Bagchi, Adam L. Buchsbaum, Michael T. Goodrich (auth.), Prosenjit Bose, Pat Morin (eds.)

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