Targeted question answering on smartphones utilizing app based user classification

State-of-the-art question answering systems are pretty successful on well-formed factual questions, however they fail on the non-factual ones. In order to investigate effective algorithms for answering non-factual questions, we deployed a crowdsourced multiple choice question answering system for playing “Who wants to be a millionaire?” game. To build a crowdsourced super-player for “Who wants to be a millionaire?”, we propose an app based user classification approach. We identify the target user groups for a multiple choice question based on the apps installed on their smartphones. Our final algorithm improves the answering accuracy by 10% on overall, and by 35% on harder questions compared to the majority voting. Our results pave the way to build highly accurate crowdsourced question answering systems.