Who wants a computer to be a millionaire?

• We focus on “Who wants to be a Millionaire?” show as multiple-choice question answering.
• The search snippet frequency model that works with a search engine is proposed.
• DBpedia, as a knowledge base, is further proposed for the task.
• Combining DBpedia with the search snippet frequency method shows the best performance.
• Our system outperforms human contestants and becomes millionaire in 6 out of 50 runs.

Competing against computers was one of the important challenges in the last decades. People like to compare their abilities with computers that are, in fact, their own invention. TV game shows provide a good opportunity for such competitions. Several attempts have been made to find out how sophisticated systems fare in game shows. An example of the task is competing in games with multiple-choice questions, such as “Who wants to be a Millionaire”.We propose an approach to this problem by using search engines and knowledge bases to automatically select the answer. The experimental results indicate the superiority of the proposed model over related work. Our proposed method achieved average winnings of $250,000 on a US question set and became a millionaire six times, out of fifty runs, which is much higher than the normal winning rate among human contestants.