Aggregating Ranked Services for Selection
In this paper we propose a method for aggregating ranked services. The ranked services are generated from multiple user requests for the same service domain. First, a service search for each individual request is performed and the search results are ranked based on the user's personalized non-functional attributes and trade-offs. Next, the ranked lists of services are then aggregated and top-ranked services are selected for the user. The proposed rank aggregation method produces a consistent ranking after aggregation because it includes the rankings given by other lists for its decision making. We propose two algorithms to deal with both complete and incomplete ranked lists during service aggregation. We also present examples with real-world services to show how the service selection based on rank aggregation works and also analyzes its performance.
K. K. Fletcher et al., "Aggregating Ranked Services for Selection," Proceedings of the 11th IEEE International Conference on Services Computing (2014, Anchorage, AK), pp. 331-338, Institute of Electrical and Electronics Engineers (IEEE), Oct 2014.
The definitive version is available at https://doi.org/10.1109/SCC.2014.51
11th IEEE International Conference on Services Computing (2014: Jun. 27-Jul. 2, Anchorage, AK)
Keywords and Phrases
Economic and social effects; Fuzzy sets; Multiple user; Non-functional; Personalized trade-off preference; Rank aggregation; Service aggregation; Service domain; Service selection; Similarity measure; Decision making
International Standard Book Number (ISBN)
Article - Conference proceedings
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