Supporting Consumers in Providing Meaningful Multi-Criteria Judgments

The huge amount of products and services that are available online, makes it difficult for consumers to identify offers which are of interest to them. Semantic retrieval techniques for Web Services address this issue, but make the unrealistic assumption that offer descriptions describe a service’s capabilities correctly and that service requests reflect a consumer’s actual requirements. As a consequence, they might produce inaccurate results. Alternative retrieval techniques such as collaborative filtering (CF) mitigate those problems, but perform not well in situations where consumer feedback is scarce. As a solution, we propose to combine both techniques. However, we argue that the multi-faceted nature Web Services imposes special requirements on the underlying feedback mechanism, that are only partially met by existing CF solutions. The focus of this paper is on how to elicit consumer feedback that can be effectively used in the context of Web Service retrieval and how to support users in that process. Our main contribution is an algorithm that suggests which service aspects should be judged by a consumer. The approach effectively adjusts to user’s ability and willingness to provide judgments and ensures that the provided feedback is meaningful and appropriate in the context of a certain service interaction.