Optimal algorithms for the online time series search problem

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

In the problem of online time series search introduced by El-Yaniv et al. [4], a player observes prices one by one over time and shall select exactly one of the prices on its arrival without the knowledge of future prices, aiming to maximize the selected price. In this paper, we extend the problem by introducing profit function. Considering two cases where the search duration is either known or unknown beforehand, we propose two optimal deterministic algorithms respectively. The models and results in the paper generalize those of El-Yaniv et al. [4].

Original languageEnglish
Title of host publicationCombinatorial Optimization and Applications - Third International Conference, COCOA 2009, Proceedings
Pages322-333
Number of pages12
DOIs
StatePublished - 2009
Event3rd International Conference on Combinatorial Optimization and Applications, COCOA 2009 - Huangshan, China
Duration: 10 Jun 200912 Jun 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5573 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Conference on Combinatorial Optimization and Applications, COCOA 2009
Country/TerritoryChina
CityHuangshan
Period10/06/0912/06/09

Keywords

  • Competitive Ratio
  • Online Algorithm
  • Profit Function
  • Time Series Search

Fingerprint

Dive into the research topics of 'Optimal algorithms for the online time series search problem'. Together they form a unique fingerprint.

Cite this