String Filtering of a Large String Collection on Mobile Devices using a Neural Network

DOI

10.2991/jcis.2006.120How to use a DOI?

Keywords

Text String, Mobile Devices, Neural Network

Abstract

String matching of a large string collection on mobile devices has been a difficult problem because of the memory space and computing speed constraints. We propose a method to efficiently determine whether a query string exists in the large string collection. The proposed method, based on a string encoder using a neural network, can perform the task in a consistent manner regardless of the number of strings in the collection. The string encoding process is executed on the server site, and the result is transmitted to the PDAs via the Internet. The server checks a remote database containing the most-updated data constantly, and thus renders the PDAs the accuracy in filtering the query strings. We conducted an experiment that simulates the stolen car license plate matching, and the results were favorable in both speed and memory space requirement.

Copyright

© 2006, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Heng Ma
AU  - Chia-Cheng Liu
PY  - 2006/10
DA  - 2006/10
TI  - String Filtering of a Large String Collection on Mobile Devices using a Neural Network
BT  - Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.120
DO  - 10.2991/jcis.2006.120
ID  - Ma2006/10
ER  -