자료유형 | 학위논문 |
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서명/저자사항 | Towards Understanding Natural Language: Semantic Parsing, Commonsense Knowledge Acquisition, Reasoning Framework and Applications. |
개인저자 | Sharma, Arpit. |
단체저자명 | Arizona State University. Computer Science. |
발행사항 | [S.l.]: Arizona State University., 2019. |
발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2019. |
형태사항 | 212 p. |
기본자료 저록 | Dissertations Abstracts International 81-02B. Dissertation Abstract International |
ISBN | 9781085691956 |
학위논문주기 | Thesis (Ph.D.)--Arizona State University, 2019. |
일반주기 |
Source: Dissertations Abstracts International, Volume: 81-02, Section: B.
Advisor: Baral, Chitta. |
이용제한사항 | This item must not be sold to any third party vendors. |
요약 | Reasoning with commonsense knowledge is an integral component of human behavior. It is due to this capability that people know that a weak person may not be able to lift someone. It has been a long standing goal of the Artificial Intelligence community to simulate such commonsense reasoning abilities in machines. Over the years, many advances have been made and various challenges have been proposed to test their abilities. The Winograd Schema Challenge (WSC) is one such Natural Language Understanding (NLU) task which was also proposed as an alternative to the Turing Test. It is made up of textual question answering problems which require resolution of a pronoun to its correct antecedent.In this thesis, two approaches of developing NLU systems to solve the Winograd Schema Challenge are demonstrated. To this end, a semantic parser is presented, various kinds of commonsense knowledge are identified, techniques to extract commonsense knowledge are developed and two commonsense reasoning algorithms are presented. The usefulness of the developed tools and techniques is shown by applying them to solve the challenge. |
일반주제명 | Artificial intelligence. |
언어 | 영어 |
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