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.
Recommended Citation
Z. Guo and J. Wang, "Information Retrieval from Large Data Sets via Multiple-Winners-Take-All," Proceedings of the 2011 IEEE International Symposium on Circuits and Systems (2011, Rio de Janeiro, Brazil), Institute of Electrical and Electronics Engineers (IEEE), Jan 2011.
The definitive version is available at https://doi.org/10.1109/ISCAS.2011.5938154
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.
Publication Date
01 Jan 2011
