Work in hybrid human-machine query processing has thus far focused on the data: gathering, cleaning, and sorting. In this paper, we address a missed opportunity to use crowd- sourcing to understand the query itself. We propose a novel hybrid human-machine approach that leverages the crowd to gain knowledge of query structure and entity relation- ships. The proposed system exploits a combination of query log mining, natural language processing (NLP), and crowd- sourcing to generate query templates that can be used to answer whole classes of different questions rather than fo- cusing on just a specific question and answer.
National Science Foundation
Expeditions in Computing