SMP 2020 情感计算论坛

 

论坛时间：2020年9月6日 上午 10：30-12：30

论坛简介：论辩 (Argumentation)研究辩论和推理的过程，是一个涉及到逻辑、哲学、语言、修辞、法律和计算机科学等多学科的研究领域。在人工智能领域研究论辩激发产生了一个新的研究方向——计算论辩(Computational Argumentation)。本次情感计算分论坛以论辩性文本的语义计算作为主题，邀请了来自学界和工业界的四位讲者介绍他们相关的研究工作。本次论坛的特邀讲者是来自宾夕法尼亚的Dan Roth教授，他会介绍他们课题组针对互联网信息革命中网络信息污染这个大课题的思考和相关研究。来自哈尔滨工业大学深圳校区的徐睿峰教授将介绍文本中的情感原因发现、立场分析和情感生成相关的研究。来自香港理工大学的李菁教授将介绍他们在论辩文本分析中使用话题和余篇分析技术的相关研究。最后，我们会邀请来自华宇信息公司的NLP专家石崇德博士，介绍法律文本中的论辩挖掘技术研究。

 

论坛主席：魏忠钰 

主席简介：魏忠钰，复旦大学大数据学院副教授，香港中文大学博士，美国德州大学达拉斯分校博士后，复旦大学数据智能与社会计算实验室（Fudan DISC）负责人，复旦大学自然语言处理团队成员。主要研究领域为自然语言处理，机器学习和社会媒体处理，专注于结合语言和视觉的多模态信息理解和生成、论辩挖掘和交叉学科应用研究。现任中文信息学会社交媒体处理专委会常务委员兼秘书，中国中文信息学会青年工作委员会委员。在自然语言处理、人工智能领域的国际会议、期刊如CL，ACL，SIGIR，EMNLP，ICML, ICLR,AAAI，IJCAI, Bioinformatics等发表学术论文60余篇。担任多个重要国际会议及期刊评审，是EMNLP 2020 多模态领域主席。获得2017年度上海市青年扬帆计划，2019年度全国社会媒体处理大会新锐奖。

 

 

论坛嘉宾：

嘉宾一

嘉宾姓名：Dan Roth，宾夕法尼亚大学 教授

嘉宾简介：Dan Roth is the Eduardo D. Glandt Distinguished Professor at the Department of Computer and Information Science, University of Pennsylvania, and a Fellow of the AAAS, the ACM, AAAI, and the ACL. In 2017 Roth was awarded the John McCarthy Award, the highest award the AI community gives to mid-career AI researchers. Roth was recognized “for major conceptual and theoretical advances in the modeling of natural language understanding, machine learning, and reasoning.” Roth has published broadly in machine learning, natural language processing, knowledge representation and reasoning, and learning theory, and has developed advanced machine learning based tools for natural language applications that are being used widely. Until February 2017 Roth was the Editor-in-Chief of the Journal of Artificial Intelligence Research (JAIR). Roth is a co-founder and the chief scientist of NexLP, Inc., a startup that leverages the latest advances in Natural Language Processing (NLP), Cognitive Analytics, and Machine Learning in the legal and compliance domains. Prof. Roth received his B.A Summa cum laude in Mathematics from the Technion, Israel, and his Ph.D. in Computer Science from Harvard University in 1995.

报告主题：Navigating Information Pollution

报告摘要：No one foresaw the truly radical impact of the Information Revolution. Most people that thought and wrote about it were quite optimistic and focused on the significant impact providing access to the world’s information would have on education, medical care, science, public policies and more. One key consequence is clear, though, and it is that of Information pollution – the contamination of information supply with irrelevant, redundant, unsolicited, incorrect, and otherwise low-value information. It is also clear that this can have, and already had, a detrimental effect on our life. Some people think about at as “fake news”, but we believe that the issues are much broader. However, this is not a forgone conclusion, We can address these consequences in creative and agreeable ways.

 I will describe a research program, rooted in natural language understanding and in reasoning, which aims at devising a computational model that will help us navigate the polluted information world. This computational mechanism could reason, over time, about sources and their expertise as well as the content they generate and its compatibility, or lack of, with our perspectives, and with other sources. This mechanism will serve as our proxy and help us judiciously handle the information pollution.

I will address and discuss the key computational challenges on the way to developing methods that can select read-worthy information. The three main objectives we would like to highlight are those of (i) identifying and understanding Perspectives expressed in documents, (ii) identifying trustworthy sources, and (iii) understanding information provenance. I will describe an experimental platform we develop in order to experiment with these new techniques.

 

嘉宾二

嘉宾姓名：徐睿峰 哈尔滨工业大学（深圳）

嘉宾简介：徐睿峰哈尔滨工业大学（深圳）计算机科学与技术学院教授。亚洲自然语言处理联合会(AFNLP)亚洲语言资源委员会主席。中国人工智能学会理事、青年工作委员会秘书长，中国计算机学会自然语言处理专业委员会副秘书长，中国中文信息学会社会媒体处理专委会常务委员、计算语言学专委会委员，IJMLC期刊副主编。长期从事自然语言处理、文本情感计算、人工智能、社交媒体挖掘、生物信息学、脑电信号处理与脑机接口等方面的研究。出版英文学术专著2本，译著1本，发表国际期刊会议论文150余篇。2017年获教育部高等院校科技进步奖二等奖。2019年获黑龙江省科学技术进步奖二等奖。2018年获中国人工智能学会优秀博士论文指导教师奖。

报告主题：文本情感理解与生成：进展与挑战

报告摘要：文本情感计算是以分析、理解、生成文本中的人类情感为对象的研究，也是人工智能研究中的核心问题之一。特别是随着社交媒体和移动互联网的发展，文本情感计算的研究范围在不断扩大，同时正在从文本情感分类与要素抽取向更深层次的文本情感理解和生成不断深入。本次报告主要介绍文本情感理解与生成领域的最近进展和体会，包括文本情感原因发现、立场分析、情感文本生成等领域的最新研究成果，以及对未来挑战的一些思考。

 

嘉宾三

嘉宾姓名：李菁，香港理工大学 助理教授

嘉宾简介: Dr. Jing Li is an Assistant Professor of the Department ofComputing, The Hong Kong Polytechnic University (PolyU) since 2019. She is amember of Data Science and AI Lab (DaSAIL) of Department of Computing and theCOMP representative for Doctor of Applied Language Sciences Programme (DALS).Before joining PolyU, she worked in the Natural Language Processing Center,Tencent AI Lab as a senior researcher from 2017 to 2019. Jing obtained her PhDdegree from the Department of Systems Engineering and Engineering Management,The Chinese University of Hong Kong in 2017. Before that, she received her B.S.degree from Department of Machine Intelligence, Peking University in 2013. Jinghas broad research interests on natural language processing, computationalsocial science, and machine learning. Particularly, she works on novelalgorithms for topic modeling, information extraction, discourse analysis, andtheir applications on social interaction understanding. Jing regularlypublished in top-tier NLP conferences and journals, such as ACL, EMNLP, NAACL,TACL, and CL. For academic services, she served as a publication co-chair inEMNLP 2020, a tutorial co-chair in ICONIP 2020, and a program committee memberin many premier conferences (e.g., ACL, EMNLP, NAACL, AAAI, IJCAI), where she receiveda best reviewer award in EMNLP 2018.

报告主题：The Effects of Topics and Discourse in Argumentation Process

报告摘要: In our world with full of uncertainty, debates and argumentationcontribute to the progress of science and society. Consequently, theunderstanding of argumentation processes will help individuals and humansociety better engage with conflicting stances and open up their minds to prosand cons. However, making sense of argumentative conversations is a dauntingtask for human readers, mostly due to the varied viewpoints and evidencecontinuously put forward and the complicated interaction structure therein; ithence presents a concrete need to develop an automatic manner to understand theargumentation processes, including who will persuade whom and why it happens. Inthis talk, we will discuss our recent studies concerning the key factormodeling in argument persuasiveness. In the first part of this talk, we willdiscuss how to track the argumentation process and learn two essential factorstherein: 1) what a discussion is centered on (i.e., topics) and 2) how theparticipants voice their opinions in arguments (i.e., discourse). Then, in thesecond part, we will discuss the roles of topics and discourse in influencingthe outcomes of an argumentation process.

 

嘉宾四

嘉宾姓名：石崇德，北京华宇元典信息服务有限公司 技术专家

嘉宾简介：石崇德，华宇元典技术专家，北京大学博士，主要从事自然语言处理相关研究，研究方向包括信息抽取、机器翻译、深度学习以及科技、法律领域文本信息处理。主持国家自然科学基金青年基金项目，参与国家自然科学基金、国家科技支撑计划、国际科技合作专项等多个国家级课题，发表论文十余篇。

报告主题：华宇元典争议焦点识别研究实践

报告摘要：在法院的庭审过程中，由于诉辩双方在证据、事实和法律适用等方面观点的不同，形成了庭审过程中双方的争议焦点。争议焦点既是庭审的主要内容，也是裁判文书的主线。本报告首先从法律业务、法律从业人员的需求角度介绍争议焦点识别的研究目标，融合业务知识、技术模型对争议焦点相关工作进行梳理和抽象，并对争议焦点数据、算法模型等进行介绍，最后对争议焦点研究中的难点和未来的研究方向进行展望。