Abstract:
Purpose – Efficiency of server side search engines is very low in cases of slow internet connections.
Therefore, this study aims to examine use of client side search tools.
Design/methodology/approach – A previously introduced client side JavaScript search model was
used. New data were obtained for response times against an array of different sized index files. A
simple linear regression model was used to obtain the limitation of file size for the search tool.
Response times for repeated searches were obtained for the client side search model and selected
server side search tools.
Findings – It was found that the search model could be used only for a small-sized data set. Still, it
was useful against server side search methods for repeated searches during a single session.
Research limitations/implications – Response time differs according to the network traffic,
connection speed, and so on. Therefore, use of the search model is context-specific.
Originality/value – The model is easy to use and maintain. Therefore, organizations that wish to
make their small data collections searchable on the web can use the model. The model is especially
suitable for users with slow internet connections who experience very low efficiency in searching large
server side databases. The paper introduces the model, solutions and technical aspects for practical
execution.
Citation:
Gamage, R., & Dong, H. (2006). JavaScript tools for online information retrieval. Online Information Review, 30(4), 380–394. https://doi.org/10.1108/14684520610686779