Collaborative Approaches to Complementing Qualitative Preferences of Agents for Effective Service Selection

Incomplete preferences of agents may render service selection ineffective. We address this problem by proposing a set of collaborative approaches to complementing agents' incomplete preferences in a qualitative way. For an agent, the approaches first find its similar agents, and then base the similar agents' qualitative preferences to complement this agent's missing preferences. We analyze and compare these approaches and provide experimental results to justify our arguments. We also compare our approach with the classic collaborative filtering and show the competitive advantages of our approach in service selection. Our work thus serves as an important step towards effective service selection.