Massachusetts Institute of Technology (MIT) and Microsoft researchers determined that search engines could use crowdsourcing to expand the range of answers they provide for users. Most Web search engines use computer-run page ranking algorithms to generate results for user submitted queries. However, this range of answers could be radically expanded through some data mining techniques and crowdsourced editing, according to MIT researcher Michael Bernstein, who presented the group's work at the Association for Computing Machinery's Conference on Human Factors in Computing Systems. "Our findings suggest that search engines can be extended to directly respond to a large new class of queries," Bernstein says. The range of answers could be radically expanded with a relative minimal additional cost by harnessing the power of crowdsourcing and contracting people to identify the answers to simple but frequently asked questions. "We are focusing on a set of queries that are somewhat popular," Bernstein says. The researchers used data mining software to analyze 75 million search queries from Microsoft's Bing search engine, looking for those queries that resulted in a click through to a single site. The researchers identified those queries that could be quickly answered and contracted workers to craft simple answers and proofread the work through Amazon's Mechanical Turk. By automating this process as much as possible, search engines can keep their costs minimal.
