Multimedia news QA: Extraction and visualization integration with multiple-source information

Recent years have witnessed the explosion of multimedia news and currently we are living in a sea of multimedia news. Faced with so huge quantities of multimedia news from all corners of the world, people are often confused and feeling overwhelmed because it takes much time and effort for them to access their desired news. As a consequence, multimedia question answering (QA) with the goal of providing precise answers to the query questions has attracted increasing attention in recent years. Towards this end, this work proposes solutions for multimedia news QA to provide an effective news information browsing experience by integrating multimedia information from multiple sources. Specifically, we first collect a large-scale multimedia news data set for question answering. And then topic analysis is used to present concise and reliable answers including textual and visual information. Experiments on the news dataset collected from multiple news websites demonstrate the encouraging performance of the proposed solutions.