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WSDM
2010
ACM
322views Data Mining» more  WSDM 2010»
14 years 6 months ago
Inferring Search Behaviors Using Partially Observable Markov (POM) Model
This article describes an application of the partially observable Markov (POM) model to the analysis of a large scale commercial web search log. Mathematically, POM is a variant o...
Kuansan Wang, Nikolas Gloy, Xiaolong Li
CHI
2011
ACM
13 years 7 days ago
YouPivot: improving recall with contextual search
According to cognitive science literature, human memory is predicated on contextual cues (e.g., room, music) in the environment. During recall tasks, we associate information/acti...
Joshua M. Hailpern, Nicholas Jitkoff, Andrew Warr,...
SC
2005
ACM
14 years 2 months ago
A Scalable Distributed Parallel Breadth-First Search Algorithm on BlueGene/L
Many emerging large-scale data science applications require searching large graphs distributed across multiple memories and processors. This paper presents a distributed breadthï¬...
Andy Yoo, Edmond Chow, Keith W. Henderson, Will Mc...
WSC
2004
13 years 10 months ago
Simulation Optimization Using Balanced Explorative and Exploitative Search
We present a new random search method for solving simulation optimization problems. Our approach emphasizes the need for maintaining the right balance between exploration and expl...
Andrei A. Prudius, Sigrún Andradótti...
ACG
2003
Springer
14 years 1 months ago
Opponent-Model Search in Bao: Conditions for a Successful Application
Abstract Opponent-Model search is a game-tree search method that explicitly uses knowledge of the opponent. There is some risk involved in using Opponent-Model search. Both the pre...
H. H. L. M. Donkers, H. Jaap van den Herik, Jos W....