Title

Information Retrieval from Large Data Sets via Multiple-Winners-Take-All

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.

Meeting Name

2011 IEEE International Symposium on Circuits and Systems, ISCAS (2011: May 15-18, Rio de Janeiro, Brazil)

Department(s)

Computer Science

Keywords and Phrases

Activation Functions; Continuous Time; Data Sets; Discrete-Time; Global Convergence; Information Retrieval Problems; Large Datasets; PageRank Algorithm; Real World Data; Single State; Web Searches

International Standard Book Number (ISBN)

978-1-4244-9473-6

International Standard Serial Number (ISSN)

0271-4302

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2011 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

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