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A weighted string pattern matching-based passage ranking algorithm for video question answering
2008
Expert systems with applications
In this paper, we present a new string pattern matching-based passage ranking algorithm for extending traditional textbased QA toward videoQA. Users interact with our videoQA system through natural language questions, while our system returns passage fragments with corresponding video clips as answers. We collect 75.6 hours videos and 253 Chinese questions for evaluation. The experimental results showed that our method outperformed six top-performed ranking models. It is 10.16% better than the
doi:10.1016/j.eswa.2007.04.008
fatcat:hn7sv3h6ybcqpge5page3rxdii