學術報告：Computational Models of Referring and their place in Natural Language Generation 　　報告人：Kees Van Deemter （阿伯丁大學） 　　時 間：2016年7月27日（周三） 上午9:30~11:30 　　地 點：軟件所5號樓四層第四會議室（中報告廳）

　　報告摘要：

　　I will start with a brief and informal introduction to Natural Language Generation (NLG), a technology that is increasingly being used in practical applications and that can also be used as a tool to sharpen our understanding of language and communication.

　　Following this informal introduction, I will focus on one component of an NLG system, namely Referring Expressions Generation, where an NLG program decides in what manner to refer to a target referent (e.g., whether to say “the red button”, or “the red button at the end of the corridor on your right”). I will introduce some classic algorithms in this area, discussing what these algorithms are able to do well and what it is that they still struggle to do. Next, I will use evidence from extensive experiments with human speakers and hearers to argue that the most difficult problems in this area arise from situations in which reference is something other than the "simple" identification of a referent through shared knowledge; I will give examples of these epistemically problematic situations, and of generation algorithms that address them.

　　The discussion of Referring Expressions Generation in this talk will reflect some of the main themes in my book “Computational Models of Referring: A Study in Cognitive Science”, which has recently appeared with MIT Press (June 2016).

　　Kees教授英文簡介：

　　I am an academic working in Computational Linguistics, a research area that belongs to both Artificial Intelligence and Cognitive Science. My main areas of expertise are Computational Semantics and Natural Language Generation. I've long taken an interest in logical and philosophical issues arising from this work; more recently I've collaborated extensively with psycholinguists interested in algorithmic models of human language production. I'm a member of Aberdeen's CLAN (Computational Linguistics in AberdeeN) group, also known as Aberdeen's Natural Language Generation group.

　　Some of my teaching is related to Natural Language Generation; other courses focus on topics in discrete mathematics that are relevant for students in Computing Science. My research centers around computational models of human communication, and around applications of these models to practical problems (e.g., automatically explaining "big data" in human language). One of my specific research interests is the computational generation of referring expressions, as when we say 'the inventor of the light bulb', or 'the large icon at the top of your screen'. I am intrigued by situations in which communication is (or appears to be) flawed, as when we use expressions that are ambiguous or vague.

　　Ambiguity was the topic of the collection "Semantic Ambiguity and Underspecification" (CSLI PUblications 1996, see review in Computational Linguistics). Vagueness is the focus of my book "Not Exactly: in Praise of Vagueness" (Oxford University Press 2010), which aims to reach people outside academia as well as within; in March 2016, a new Chinese translation of this book has come out.

　　Kees教授中文簡介：

　　Kees Van Deemter教授1991年畢業于荷蘭阿姆斯特丹大學，獲得博士學位，1992年至1993年作為博士后在斯坦福大學工作兩年。1994年至2004年擔任英國布萊頓大學信息技術研究中心的首席研究員。2004年以來，供職于英國阿伯丁大學計算科學系，擔任系主任職務，2012年獲得終身教授職位。Kees教授長期從事自然語言生成方面的研究，他帶領的自然語言生成實驗室處于世界一流研究水平。Kees教授的研究領域包括：自然語言生成體系、指代表達及產生及指代消解等方面，取得了頗豐的研究成果。Kees教授主持和參與英國工程與物理科學研究委員會項目6項，歐洲科學基金會項目1項，與諾基亞等高科技公司也有項目合作。獨立出版著作2部，與他人合著出版著作4部；發表科技論文100余篇。