Abstract
The decision making process of selecting a service is very complex. Current recommendation systems make a generic recommendation to users regardless of their personal standards. This can result in a misleading recommendation because different users normally have different standards in evaluating services. Some of them might be harsh in their assessment while others are lenient. In this paper, we propose a standard-based approach to assist users in selecting their preferred services. To do so, we develop a judgement model to detect users’ standards then utilize them in a service recommendation process. To study the accuracy of our approach, 65536 service invocation results are collected from 3184 service users. The experimental results show that our proposed approach achieves better prediction accuracy than other approaches.
Highlights
Different users have different personal standards in evaluating services
We have proposed a standard-based recommender system
Because understanding human preferences are complex and may depend on their personal standards, these standards must be considered in the recommender system
Summary
Different users have different personal standards in evaluating services. The averaging approach is simple; it does not consider how personal user standard may affect choosing services. This is because Averaging-All approach neglects the relevance of ratings; irrelevant ratings maybe aggregated, resulting in inaccurate service recommendation. We propose a standard-based approach to assist users select their preferred services. To study the accuracy of our approach, 65536 service invocation results are collected from 3184 service users. The experimental results show that our proposed approach achieves better prediction accuracy than the Averaging-All approach.
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