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Modeling Physical Causality of Action Verbs for Grounded Language Understanding
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Modeling Physical Causality of Action Verbs for Grounded Language Understanding. |
| 개인저자 | Gao, Qiaozi. |
| 단체저자명 | Michigan State University. Computer Science - Doctor of Philosophy. |
| 발행사항 | [S.l.]: Michigan State University., 2019. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2019. |
| 형태사항 | 119 p. |
| 기본자료 저록 | Dissertations Abstracts International 81-03A. Dissertation Abstract International |
| ISBN | 9781085751063 |
| 학위논문주기 | Thesis (Ph.D.)--Michigan State University, 2019. |
| 일반주기 |
Source: Dissertations Abstracts International, Volume: 81-03, Section: A.
Advisor: Chai, Joyce Y. |
| 이용제한사항 | This item must not be sold to any third party vendors.This item must not be added to any third party search indexes. |
| 요약 | Building systems that can understand and communicate through human natural language is one of the ultimate goals in AI. Decades of natural language processing research has been mainly focused on learning from large amounts of language corpora. However, human communication relies on a significant amount of unverbalized information, which is often referred as commonsense knowledge. This type of knowledge allows us to understand each other's intention, to connect language with concepts in the world, and to make inference based on what we hear or read. Commonsense knowledge is generally shared among cognitive capable individuals, thus it is rarely stated in human language. This makes it very difficult for artificial agents to acquire commonsense knowledge from language corpora. To address this problem, this dissertation investigates the acquisition of commonsense knowledge, especially knowledge related to basic actions upon the physical world and how that influences language processing and grounding.Linguistics studies have shown that action verbs often denote some change of state (CoS) as the result of an action. For example, the result of "slice a pizza" is that the state of the object (pizza) changes from one big piece to several smaller pieces. However, the causality of action verbs and its potential connection with the physical world has not been systematically explored. Artificial agents often do not have this kind of basic commonsense causality knowledge, which makes it difficult for these agents to work with humans and to reason, learn, and perform actions.To address this problem, this dissertation models dimensions of physical causality associated with common action verbs. Based on such modeling, several approaches are developed to incorporate causality knowledge to language grounding, visual causality reasoning, and commonsense story comprehension. |
| 일반주제명 | Computer science. Linguistics. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
