자료유형 | 학위논문 |
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서명/저자사항 | Data and Methods for Reference Resolution in Different Modalities. |
개인저자 | Guha, Anupam. |
단체저자명 | University of Maryland, College Park. Computer Science. |
발행사항 | [S.l.]: University of Maryland, College Park., 2017. |
발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2017. |
형태사항 | 143 p. |
기본자료 저록 | Dissertation Abstracts International 79-07B(E). Dissertation Abstract International |
ISBN | 9780355627701 |
학위논문주기 | Thesis (Ph.D.)--University of Maryland, College Park, 2017. |
일반주기 |
Source: Dissertation Abstracts International, Volume: 79-07(E), Section: B.
Advisers: Yiannis Aloimonos |
이용제한사항 | This item is not available from ProQuest Dissertations & Theses. |
요약 | One foundational goal of artificial intelligence is to build intelligent agents which interact with humans, and to do so, they must have the capacity to infer from human communication what concept is being referred to in a span of symbols. They |
요약 | A central theme throughout this thesis is the paucity of data in solving hard problems of reference, which it addresses by designing several datasets. To investigate hard text coreference this dissertation analyses a domain of coreference heavy |
일반주제명 | Computer science. Artificial intelligence. |
언어 | 영어 |
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: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |