Name
Title | ||
|---|---|---|
1 Billion Pages = 1 Million Dollars? mining the web to play "who wants to be a millionaire?" |
Abstract | ||
|---|---|---|
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 Millionaire CD-ROM, 3rd edition--general-interest trivia questions often about popular culture and common knowledge. The decision-making module chooses from allowable actions in the game in order to maximize expected risk-adjusted winnings, where the estimated probability of answering correctly is a function of past performance and confidence in correctly answering the current question. When given a six question head start (i.e., when starting from the $2,000 level), we find that the system performs about as well on average as humans starting at the beginning. Our system demonstrates the potential of simple but well-chosen techniques for mining answers from unstructured information such as the web. |
Year | Venue | Keywords |
|---|---|---|
2012 | UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence | billion pages,abc tv game show,question-answering module,question head start,multiple information retrieval algorithm,general-interest trivia question,current question,decision-making module,millionaire cd-rom,question-answering module utilizes,million dollars,unstructured information,common knowledge,popular culture,ensemble learning,information retrieval,search engine,question answering |
DocType | Volume | ISBN |
Journal | abs/1212.2477 | 0-127-05664-5 |
Citations | PageRank | References |
12 | 0.89 | 19 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shyong K. Lam | 1 | 1470 | 104.02 |
| kwokyan lam | 2 | 12 | 0.89 |
| David M. Pennock | 3 | 3823 | 451.85 |
| Dan Cosley | 4 | 3239 | 260.74 |
| Steve Lawrence | 5 | 6194 | 872.30 |