On approximation of bookmark assignments

Yuichi Asahiro, Eiji Miyano, Toshihide Murata, Hirotaka Ono

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Consider a rooted directed acyclic graph G = (V, E) with root r, representing a collection V of web pages connected via a set E of hyperlinks. Each node v is associated with the probability that a user wants to access the node v. The access cost is defined as the expected number of steps required to reach a node from the root r. A bookmark is an additional shortcut from r to a node of G, which may reduce the access cost. The bookmark assignment problem is to find a set of bookmarks that achieves the greatest improvement in the access cost. For the problem, the paper presents a polynomial time approximation algorithm with factor (1 -1/e), and shows that there exists no polynomial time approximation algorithm with a better constant factor than (1-1/e) unless NP ⊆ DTIME(NO(log log N)), where N is the size of the inputs.

Original languageEnglish
Title of host publicationMathematical Foundations of Computer Science 2007 - 32nd International Symposium, MFCS 2007, Proceedings
Pages115-124
Number of pages10
Publication statusPublished - Dec 1 2007
Event32nd International Symposium on Mathematical Foundations of Computer Science, MFCS 2007 - Cesky Krumlov, Czech Republic
Duration: Aug 26 2007Aug 31 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4708 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other32nd International Symposium on Mathematical Foundations of Computer Science, MFCS 2007
CountryCzech Republic
CityCesky Krumlov
Period8/26/078/31/07

Fingerprint

Assignment
Approximation algorithms
Approximation
Vertex of a graph
Polynomials
Polynomial-time Algorithm
Approximation Algorithms
Costs
Roots
Websites
Directed Acyclic Graph
Assignment Problem

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Asahiro, Y., Miyano, E., Murata, T., & Ono, H. (2007). On approximation of bookmark assignments. In Mathematical Foundations of Computer Science 2007 - 32nd International Symposium, MFCS 2007, Proceedings (pp. 115-124). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4708 LNCS).

On approximation of bookmark assignments. / Asahiro, Yuichi; Miyano, Eiji; Murata, Toshihide; Ono, Hirotaka.

Mathematical Foundations of Computer Science 2007 - 32nd International Symposium, MFCS 2007, Proceedings. 2007. p. 115-124 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4708 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Asahiro, Y, Miyano, E, Murata, T & Ono, H 2007, On approximation of bookmark assignments. in Mathematical Foundations of Computer Science 2007 - 32nd International Symposium, MFCS 2007, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4708 LNCS, pp. 115-124, 32nd International Symposium on Mathematical Foundations of Computer Science, MFCS 2007, Cesky Krumlov, Czech Republic, 8/26/07.
Asahiro Y, Miyano E, Murata T, Ono H. On approximation of bookmark assignments. In Mathematical Foundations of Computer Science 2007 - 32nd International Symposium, MFCS 2007, Proceedings. 2007. p. 115-124. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Asahiro, Yuichi ; Miyano, Eiji ; Murata, Toshihide ; Ono, Hirotaka. / On approximation of bookmark assignments. Mathematical Foundations of Computer Science 2007 - 32nd International Symposium, MFCS 2007, Proceedings. 2007. pp. 115-124 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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