by Jožef Stefan Institute, Ljubljana Slovenia
Abstract: The acquisition of high-quality structured knowledge that is immediately useful for reasoning algorithms has been a longstanding goal of the artificial intelligence research community. The recent advances in crowdsourcing, the sheer number of Internet users, and the commercial availability of supporting platforms have led to a new set of tools to tackle the problem. Although numerous systems and methods for crowdsourced knowledge acquisition have been developed and solve the problem of human resources, issues such as task preparation, financial cost, finding the right crowd, and the consistency and quality of the acquired knowledge persist. In this paper we propose a new approach to address this deficit by exploiting an existing knowledge base to drive the acquisition process, address the right people, and check their answers for consistency. We tested the viability of the approach in experiments with real users, a working platform and commonsense knowledge.