与6位图灵奖得主和100多位专家

共同探讨人工智能的下一个十年

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2020年6月21-24日，第二届北京智源大会（官网：https://2020.baai.ac.cn）将邀请包括6位图灵奖获得者在内的上百位人工智能领袖，一起回顾过去，展望未来，深入系统探讨“人工智能的下一个十年”。本次大会将开设19个专题论坛，主题涵盖人工智能数理基础、自然语言处理、智能体系架构与芯片、人工智能伦理治理与可持续发展、机器学习、智能信息检索与挖掘、认知神经基础、机器感知、决策智能、AI医疗、AI创业、AI交通、AI+大数据+防疫、AI框架、图神经网络、知识智能、强化学习、青年科学家机器学习前沿，以及AI科技女性，遍历人工智能基础研究及创新应用，结合时局解析人工智能最新动态，探索未来发展方向。

我们将带你走进各个分论坛，领略嘉宾风采、洞悉前沿趋势。今天介绍的是将于6月23日上午举行的智能信息检索与挖掘专题论坛。

论坛主席

文继荣

智源首席科学家,中国人民大学信息学院院长，博士生导师。于中科院计算所获得博士学位，同年加入微软亚洲研究院，后担任高级研究员和互联网搜索与数据挖掘组主任。在微软亚洲研究院工作的14年中，获得50多项美国专利，其中一些成果已经被用于重要的微软产品中(如微软搜索引擎Bing)。所领导的研究团队开发出了微软学术搜索、人立方、产品搜索等有影响力的互联网应用。在国际著名会议和期刊上发表了一百多篇论文，担任过许多国际会议和研讨会的程序委员和主席。是信息检索领域主要期刊ACM Transactions on Information Systems(TOIS)的副主编(Associate editor)。

演讲主题及嘉宾介绍

1. 智能搜索：从技术工具到思维心智

议题简介：搜索和智能紧密联结，浑然一体，搜索皆智能，智能皆搜索。智能搜索已经成为信息时代无时无刻、无处不在的基本工具。智能搜索的广泛应用正在迅速改变我们的思维和心智，并孕育着下一代热情经济的发展。智能搜索要造福全人类，必须解决一系列挑战，包括本地化、可理解性、文化、公平、隐私保护、复杂性、安全性等许多方面，远远超过人工智能和技术的范畴，需要我们以更开放的视野和更广阔的包容心去认知、研究和创造。

演讲嘉宾：裴健

加拿大西门菲莎大学教授，加拿大皇家科学院和加拿大工程院院士。他的研究领域包括数据科学与工程、数据挖掘、数据处理系统、医疗信息学、企业数据战略、数据资产管理等。他发表了两百多篇学术论文和专著，被引用九万六千多次。

2. Challenges in Combating Disinformation on Social Media

议题简介：In recent years, disinformation has become a global phenomenon, particularly so during times of crises such as the pandemic of COVID-19. Disinformation appears in a gamut of types from scams to conspiracy theories, to political campaigns, and to rumors. The wide dissemination of disinformation can have harmful impact on individuals and the society. Despite the recent progress in detecting fake news, disinformation detection and mitigation remains a defying task due to its scale, complexity, diversity, speed, and costs of fact-checking or annotation, as well as social and psychological factors. In this talk, we look at some lessons learned when exploring strategies of detecting disinformation and fake news, and discuss challenges in disinformation research and the pressing need for interdisciplinary research. This talk is mainly based on Kai Shu’s research at ASU.

演讲嘉宾：刘欢

Professor of Computer Science and Engineering at Arizona State University. Before he joined ASU, he worked at Telecom Australia Research Labs and was on the faculty at National University of Singapore. He is a co-author of a text, Social Media Mining: An Introduction, Cambridge University Press and a recent monograph, Detecting Fake News on Social Media, Morgan & Claypool Publishers. He is a founding organizer of the International Conference Series on Social Computing, Behavioral-Cultural Modeling, and Prediction, and Field Chief Editor of Frontiers in Big Data  and its Specialty Chief Editor of Data Mining and Management. He is a Fellow of ACM, AAAI, AAAS, and IEEE. More information can be found at http://www.public.asu.edu/~huanliu.

3. Open-World AI and Continual Learning

议题简介：The classic machine learning (ML) paradigm learns in isolation, which is only suitable for well-defined narrow tasks in closed environments. It is far from sufficient for AI systems such as self-driving cars and chatbots that need to work in the real-world dynamic and open environment that is full of unknowns. We humans learn comfortably in such environments. We learn continuously, accumulate the learned knowledge, and learn more and better in a self-motivated and self-supervised manner in our interactions with other humans and the physical environment. Lifelong/continual learning in the open world aims to imitate this human continuous learning capability. In this talk, I will discuss open-world AI and continual learning using self-driving cars and chatbots as applications. These systems seem to need the human-level of intelligence to work well, which the current AI and/or ML algorithms are unable to provide.

演讲嘉宾：刘兵

Chair professor at Peking University (on leave from the University of Illinois at Chicago). He received his Ph.D. in AI from the University of Edinburgh. His research interests include lifelong machine learning, sentiment analysis, natural language processing (NLP), and data mining. He has published extensively in top conferences and journals, and authored four books. Three of his papers received Test-of-Time awards: two from SIGKDD and one from WSDM. Another paper also received Test-of-Time award - honorable mention from WSDM. Some of his work has been widely reported in the international press, including a front-page article in The New York Times. He is the recipient of 2018 ACM SIGKDD Innovation Award. He served as the Chair of ACM SIGKDD from 2013-2017, as program chair of many leading data mining conferences, including KDD, ICDM, CIKM, WSDM, SDM, and PAKDD, and as area/track chair or senior PC member of numerous NLP, AI, Web, and data mining conferences. He is a Fellow of ACM, AAAI, and IEEE.

4. Multimodal Conversational Search

议题简介：Information search has been evolving from mostly unidirectional and text-based to interactive and multimodal. Recently, there is also a growing interest in all matters conversational. By incorporating multimodal conversation, it offers users a natural way to query the system by combining text/speech, images/videos and possibly gesture. It also helps to tackle the basic asymmetric problem in search by injecting conversation to resolve ambiguities in search and recommendation. However, the evolution from traditional IR to conversational IR faces many challenges. Among them are the need to develop new models and framework to: model multimodal context and history, integrate domain knowledge and user models; conduct interactive IR and QA, develop intervention strategy to incorporate conversation into browsing; and integrate conversation with recommendation, database search and Web search. Moreover, there are the issues of resources, methodologies and biasness in evaluating (multi-turn) conversational search systems. This talk presents current research in tackling these problems with pointers towards future research.

演讲嘉宾：蔡达成

新加坡国立大学计算机学院创院院长、KITHCT讲席教授。自2010年至今担任清华大学-新加坡国立大学下一代搜索联合研究中心新方主任，长期担任新加坡政府IT项目管理认证与评估委员会(CITPM)的主席，是国际知名计算机科学家。在多媒体、文本和社交媒体分析与检索领域做出了一系列开创性工作，获得IEEE Multimedia Magazine和ACM Multimedia等重要国际刊物和会议的10项最佳论文奖，获得2015年国际计算机协会多媒体专业委员会（ACM SIGMM）杰出技术贡献奖，曾担任顶级国际会议ACM Multimedia、ACM SIGIR 的大会主席，是国际计算机图形学协会（Computer Graphics Society）、国际图像视频检索会议（CIVR）、国际多媒体建模会议（International Multimedia Modeling Conference）的指导委员会成员。

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