RaaS - Ranking as a Service

Abstract

Choice is a pervasive feature of social life that profoundly affects us. Ranking results can be used as a reference to help people make a correct choice. But there are two problems. One problem is that fixed ranking results instead of the ranking methods are provided to people by service providers as a reference when making choice at most time. For example, TIMES World University Rankings can be used as a reference when choosing a college. However, in the numerous factors that affect objects ranking, people have their own understanding on the effect of each factor on objects ranking. Using mobile phone-selection as a practical case, some people think performance of a mobile phone is more important, while others hold the view that appearance of a mobile phone is more attractive. What's more, there are many ranking methods proposed, such as The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and expert marking. Using only one kind of ranking methods for object ranking may lead to over objective or subjective ranking results. Although various ranking algorithm are studied, very little is known about the detailed development and deployment of the ranking services. This paper proposes a comprehensive solution of Ranking as a Service (RaaS), with the manifold contributions: Firstly, we use combination weighting method in RaaS and it can overcome the defects of subjective and objective weighting methods. Secondly, we develop ranking service APIs that bring convenience to people when making choices. Thirdly, ranking service provides ranking results for people according to their own understanding on the effect of each factor on objects ranking. Fourthly, this paper is arguably the first one that proposes using Ranking as a Service. Finally, we evaluate and analyze the proposed strategies and technologies in accordance to the experimental results.