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Maximizing Insight from Modern Economic Analysis
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Maximizing Insight from Modern Economic Analysis. |
| 개인저자 | Antenucci, Dolan. |
| 단체저자명 | University of Michigan. Computer Science and Engineering. |
| 발행사항 | [S.l.]: University of Michigan., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 186 p. |
| 기본자료 저록 | Dissertation Abstracts International 79-12B(E). Dissertation Abstract International |
| ISBN | 9780438127180 |
| 학위논문주기 | Thesis (Ph.D.)--University of Michigan, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
Adviser: Michael John Cafarella. |
| 요약 | The last decade has seen a growing trend of economists exploring how to extract different economic insight from "big data" sources such as the Web. As economists move towards this model of analysis, their traditional workflow starts to become in |
| 요약 | This dissertation presents several systems and methodologies that bring economists closer to this ideal workflow, helping them address many of the challenges faced in transitioning to working with big data sources like the Web. To help users gen |
| 일반주제명 | Computer science. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
