Information retrieval from large data sets via multiple-winners-take-all

Zhishan Guo, Jun Wang

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

9 Citations (Scopus)

Abstract

Recently, a continuous-time k-winners-take-all (kWTA) network with a single state variable and a hard-limiting activation function and its discrete-time counterpart were developed. These kWTA networks have proven properties of finite-time global convergence and simple architectures. In this paper, the kWTA networks are applied for information retrieval, such as web search. The weights or scores of pages in two real-world data sets are calculated with the PageRank algorithm, based on which experimental results of kWTA networks are provided. The results show that the kWTA networks converge faster as the size of the problem grows, which renders them as a promising approach to large-scale data set information retrieval problems.

Original languageEnglish
Title of host publication2011 IEEE International Symposium of Circuits and Systems, ISCAS 2011
Pages2669-2672
Number of pages4
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2011 IEEE International Symposium of Circuits and Systems, ISCAS 2011 - Rio de Janeiro, Brazil
Duration: 15 May 201118 May 2011

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
ISSN (Print)0271-4310

Conference

Conference2011 IEEE International Symposium of Circuits and Systems, ISCAS 2011
Country/TerritoryBrazil
CityRio de Janeiro
Period15/05/1118/05/11

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