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Modeling users’ online behavior has great benefit for many e-Commerce web sites and search engines. In the context of software service selection, if we could understand users’ personal preferences, we could rank the services in a more satisfactory way. Many users have some general preferences on the desired values of non-functional properties (e.g. provider history, service popularity, etc.) of services, even if they may not explicitly define them. In this paper, we propose to build user profiles on these non-functional preferences, and then use them to personalize the ranking results for individual users. Our experiment showed that personalized ranking could promote the services matching with the user preferred non-functional values to higher positions, making it easier for users to identify their desired services. We also tested how different factors impact the degree of improvement on the ranking accuracy.

Item Type:	Refereed Conference Paper
Keywords:	service ranking, service selection, non-functional preference, user modelling, personalisation
Research Division:	Information and Computing Sciences
Research Group:	Library and Information Studies
Research Field:	Human Information Behaviour
Objective Division:	Expanding Knowledge
Objective Group:	Expanding Knowledge
Objective Field:	Expanding Knowledge in the Information and Computing Sciences
UTAS Author:	Chi, C (Dr Chi-Hung Chi)
ID Code:	116553
Year Published:	2012
Deposited By:	Information and Communication Technology
Deposited On:	2017-05-12
Last Modified:	2017-06-21
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