{"paper":{"title":"1 Billion Pages = 1 Million Dollars? Mining the Web to Play \"Who Wants to be a Millionaire?\"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.IR","authors_text":"Dan Cosley, David M Pennock, Shyong (Tony) K. Lam, Steve Lawrence","submitted_at":"2012-10-19T15:06:15Z","abstract_excerpt":"We exploit the redundancy and volume of information on the web to build a     computerized player for the ABC TV game show 'Who Wants To Be A Millionaire?'     The player consists of a question-answering module and a decision-making     module. The question-answering module utilizes question transformation     techniques, natural language parsing, multiple information retrieval     algorithms, and multiple search engines; results are combined in the spirit of     ensemble learning using an adaptive weighting scheme. Empirically, the system     correctly answers about 75% of questions from the "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1212.2477","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}