VLDB Database School (China) VLDB 中国数据库学院

Transcription

1 VLDB Database School (China) VLDB 中国数据库学院 2012 Summer School 2012 年暑期学校 July 23 July 27, 年 7 月 23 日 7 月 27 日 Kunming, China 中国 昆明 VLDB Database School (China) School of Information Science and Engineering Yunnan University VLDB 中国数据库学院云南大学信息学院

2 Contents 1. Introduction Schedule Lecturers 云南大学信息学院简介 云南大学及周边地图 学生管理规章 生活服务 旅游服务

3 1. Introduction VLDB (Very Large Data Bases) Database School (China) was sponsored by VLDB endowment, subordinated by China Computer Federation Technical Committee on Database (CCF-TCDB). VLDB database school provides a forum for professors, scholars and senior graduate students in database theory and technique research. Famous database scientists in international database paradigm are invited to give lectures during each summer vacation. From 2002, VLDB database summer school has been successfully held in Soochow University, East China Normal University, North East University, etc VLDB summer school will be held in Yunnan University, Kunming, China, from July 23 to July 27, We have invited Prof. Gerhard Weikum and Prof. Michael Franklin as the lecturers of this summer school. Prof. Gerhard Weikum is a Scientific Director at the Max Planck Institute for Informatics in Saarbruecken, Germany. Prof. Michael Franklin is the Thomas M. Siebel Professor of Computer Science and Director of the Algorithms, Machines, and People Laboratory (AMPLab) at UC Berkeley. The topic of this summer school is knowledge harvesting in big data, including the course of Knowledge Harvesting from Text and Web Sources given by Prof. Gerhard Weikum and that of Making Sense at Scale - Advances in Big Data Analytics given by Prof. Michael Franklin. Each of these two parts of courses will cover about 2.5 days. It is this year that Yunnan University will celebrate her birthday of 90 years old. It s our great pleasure to organize and honor this summer school exactly at this important and commemorative time. The website of this summer school is as follows: 2

4 2. Schedule July 22, 2012 Registration (10:00 22:00) Venue: Yunnan University Hotel July 23, 2012 (Day 1) 8:30 9:00 Opening Welcome Venue: 2 nd Floor Lecturing room, Science Building of Yunnan University 9:00 10:00 Prof. Gerhard Weikum Title: Knowledge Harvesting from Text and Web Sources Venue: # 105 Science Building of Yunnan University Session 1: (1) Motivation of Knowledge Bases and their Automatic Construction; (2) Machine Knowledge Coffee Break (Time: 10:00 10:30) 10:30 12:00 Session 1: Knowledge Harvesting: Entities and Classes Lunch (Time: 12:00 13:30, Venue: Dining Hall ( 食堂 )) 14:00 15:30 Session 2: Assignments Coffee Break (Time: 15:30 16:00) 16:00 17:30 Session 2: Knowledge Harvesting: Relational Facts Reception (Time: 18:00 20:00, Venue: YinXing Yuan ( 云大银杏苑餐厅 )) July 24, 2012 (Day 2) 8:30 10:00 Session 3: (1) Advanced Knowledge: Open-Domain Extraction; (2) Advanced Knowledge: Temporal, Multilingual, Multimodal, Commonsense Coffee Break (Time: 10:00 10:30) 10:30 12:00 Session 3: Search and Ranking of Knowledge Lunch (Time: 12:00 13:30, Venue: Dining Hall ( 食堂 )) 14:00 15:30 Session 4: Assignments Coffee Break (Time: 15:30 16:00) 16:00 17:30 Session 4: Discussion Dinner (Time: 18:00 19:00, Venue: Dining Hall ( 食堂 )) July 25, 2012 (Day 3) 8:30 10:00 Session 5: Named-Entity Disambiguation Coffee Break (Time: 10:00 10:30) 10:30 12:00 Session 5: Entity Linkage Lunch (Time: 12:00 13:30, Venue: Dining Hall ( 食堂 )) 3

5 14:00 15:30 Prof. Michael Franklin Title: Making Sense at Scale - Advances in Big Data Analytics Venue: # 105 Science Building of Yunnan University Session 1: Big Data - Introduction Coffee Break (Time: 15:30 16:00) 16:00 17:30 Session 1: Database Analytics and Data Warehouses Banquet (Time:18:30 20:30, Venue: YuanNong XinCun,Yunnan University Hotel ( 云大宾馆原农新村餐厅 )) July 26, 2012 (Day 4) 8:30 10:00 Session 2: Databases vs. NoSQL Coffee Break (Time: 10:00 10:30) 10:30 12:00 Session 2: Stream Processing Lunch (Time: 12:00 13:30, Venue: Dining Hall ( 食堂 )) 14:00 15:30 Session 3: Data Integration / Dataspaces Coffee Break (Time: 15:30 16:00) 16:00 17:30 Session 3: Data Science Overview Dinner (Time: 18:00 19:00, Venue: Dining Hall ( 食堂 )) July 27, 2012 (Day 5) 8:30 10:00 Session 4: Algorithms, Machines and People Coffee Break (Time: 10:00 10:30) 10:30 12:00 Session 4: Crowdsourcing I Lunch (Time: 12:00 13:30, Venue: Dining Hall ( 食堂 )) 14:00 15:30 Session 5: Crowdsourcing II Coffee Break (Time: 15:30 16:00) 16:00 17:00 Session 5: Crowdsourcing III and Wrap-Up 17:00 17:30 Closing Dinner Time (Time: 17:20 19:20, Venue: Dining Hall ( 食堂 )) 联系人及联系电话 (Contacts and Phones): 岳昆 ( 组委会主席 ) / YUE Kun (Organization Chair):(86) 李劲 ( 录取 毕业 ) / LI Jin (Acceptance, graduation):(86) 钱文华 ( 资料 课程 ) / QIAN Wenhua (Materials, courses):(86) 赵征鹏 ( 用餐 住宿 ) / ZHAO Zhengpeng (Accommodation):(86)

6 Note: Participants are encouraged to use their own notebook computers for assignments or experiments. Wireless network can be available in the lecturing room. Participants can ideally work with the following URLs for the courses given by Prof. Gerhard Weikum: Wikipedia: en.wikipedia.org YAGO: yago-knowledge.org Dbpedia: dbpedia.org Freebase: freebase.com Entitycube: research.microsoft.com/en-us/projects/entitycube/ NELL: rtw.ml.cmu.edu DeepDive: Probase: research.microsoft.com/en-us/projects/probase/ KnowItAll / ReVerb: openie.cs.washington.edu reverb.cs.washington.edu PATTY: BabelNet: lcl.uniroma1.it/babelnet WikiNet: ConceptNet: conceptnet5.media.mit.edu Linked Open Data: linkeddata.org RDF-Express: sigma: sig.ma sindice: sindice.com sameas: sameas.org Aida: Dbpedia Spotlight: Open Calais: 5

7 3. Lecturers Prof. Gerhard Weikum Course Title: Knowledge Harvesting from Text and Web Sources. Course Abstract: The proliferation of knowledge- sharing communities such as Wikipedia and the progress in scalable information extraction from Web and text sources has enabled the automatic construction of very large knowledge bases. Recent endeavors of this kind include academic research projects such as DBpedia, KnowItAll, Probase, ReadTheWeb, and YAGO, as well as industrial ones such as Freebase and Trueknowledge. These projects provide automatically constructed knowledge bases of facts about named entities, their semantic classes, and their mutual relationships. Such world knowledge in turn enables cognitive applications and knowledge-centric services like disambiguating natural-language text, deep question answering, and semantic search for entities and relations in Web and enterprise data. This course presents state-of-the-art methods, recent advances, research opportunities, and open challenges along this avenue of knowledge harvesting and its applications. Biography: Gerhard Weikum is a Scientific Director at the Max Planck Institute for Informatics in Saarbruecken, Germany, where he is leading the department on databases and information systems. He is also an Adjunct Professor at Saarland University, and a principal investigator of the DFG Cluster of Excellence on Multimodal Computing and Interaction. Earlier he held positions at Saarland University in Saarbruecken, Germany, at ETH Zurich, Switzerland, at MCC in Austin, Texas, and he was a visiting senior researcher at Microsoft Research in Redmond, Washington. He graduated from the University of Darmstadt, Germany. Gerhard Weikum's research spans transactional and distributed systems, self-tuning database systems, DB&IR integration, and the automatic construction of knowledge bases from Web and text sources. He co-authored a comprehensive textbook on transactional systems, received the VLDB 10-Year Award for his work on automatic DB tuning, and is one of the creators of the YAGO knowledge base. Gerhard Weikum is an ACM Fellow, a Fellow of the German Computer Society, and a member of the German Academy of Science and Engineering. He has served on various editorial boards, including ACM Transactions on Database Systems and Communications of the ACM, and as program committee chair of conferences like ACM SIGMOD, Data Engineering, and CIDR. From 2003 through 2009 he was president of the VLDB Endowment. He received the ACM SIGMOD Contributions Award in

8 Prof. Michael Franklin Course Title: Making Sense at Scale - Advances in Big Data Analytics Course Abstract: The analysis and understanding of data are becoming increasingly important to organizations of all types. As organizations collect more and more data, they require analytics systems that can scale with data volumes, but the challenge of "Big Data" analytics is more than simply one of data size. Rather, as the scope of data analysis widens, issues such as data integration, data cleaning, and dealing with ambiguity and incompleteness in both queries and the underlying data are exacerbated. This combination of size and complexity make it difficult for users to obtain answers to their data-driven questions within their time, cost and quality constraints. In this set of lectures we will survey recent approaches to processing large volumes of data from both Relational Database and Systems perspectives. Topics include: Scalable Database Systems, Real-Time and Stream Query Processing, NoSQL Approaches, Flexible Data Integration, Architectures for Scalable Machine Learning and Crowdsourced Query Processing. Biography: Michael Franklin is the Thomas M. Siebel Professor of Computer Science and Director of the Algorithms, Machines, and People Laboratory (AMPLab) at UC Berkeley. AMPLab is a cross-disciplinary collaboration integrating machine learning, large-scale cluster computing and crowdsourcing to develop new approaches to big data analytics, supported by 18 leading technology companies and a White House-announced NSF Expeditions in Computing Award. His on-going research projects are in the areas of data stream processing and continuous analytics, scalable query processing, large-scale sensing environments, data integration, hybrid human/computer data processing systems, and cross-data center consistency protocols. He is a Fellow of the Association for Computing Machinery and recipient of the NSF CAREER award and the ACM SIGMOD "Test of Time" award. His recent awards include a Best Paper award at NSDI 2012, Best Demo award at VLDB 2011 and the 2011 Outstanding Advisor Award from the Computer Science Graduate Student Association at Berkeley. He is currently serving as a committee member on the U.S. National Academy of Sciences study on Analysis of Massive Data. He was the founder and CTO of Truviso, Inc. a streaming data analytics company that was recently acquired by Cisco Systems to provide real-time analytics for Network Analytics and other data-in-motion applications. 7

9 4. 云南大学信息学院简介 云南大学信息学院是在整合原有的信息与电子科学系 计算机科学系和云南大学计算中心的基础上于 1998 年 4 月组建成立 学院现有计算机科学与工程 通信工程 信息与电子科学 电子工程 4 个系, 还有 1 个高性能计算中心 1 个校级公共计算机教学部 1 个校级实验中心和 1 个新技术研究所 师资队伍方面, 学院现有教职工 110 余人, 其中正 副教授 50 余人, 博士研究生导师 10 人, 云南省中青年学术带头人和技术创新人才 10 余人, 聘请了 10 多名国内外知名专家学者作为学院的兼职教授, 聘请了一批 IT 企业的专家作为兼职研究员, 参与学院的教学和科研工作 学科学位点建设方面, 计算机科学与技术 和 信息与通信工程 是云南省重点学科, 计算机科学与技术 被列为云南省十二五拟新增一级学科博士点, 通信网络与智能计算 是云南省高校重点实验室 拥有信息与通信工程一级博士学位授权点 ( 包括计算智能与知识发现 海量数据管理 智能信息处理, 高性能计算 分布式系统 通信网络理论与无线通信技术 网络协议工程等方向 ) 拥有通信与信息系统 计算机软件与理论 计算机应用技术 信号与信息处理 人工智能与模式识别 计算机系统结构 生物医学工程 电路与系统 检测技术与自动化装置 控制工程 10 个硕士学位授权点, 还拥有电子与通信工程和计算机技术 2 个工程硕士专业学位授权点, 在校各类研究生人数已达 700 余人 人才培养方面, 信息学院自主培养了云南省第一个 通信工程 和第一个 计算机科学与技术 领域的博士生 ; 培养了云南省三分之二以上的 IT 人才, 包括云南省自主培养的近 20 名具有博士学位的信息技术人才 设有计算机科学与技术 ( 省级重点专业 国家级特色专业 ) 通信工程( 省级重点专业 ) 电子信息科学与技术( 省级重点专业 ) 电子信息工程 4 个本科专业, 在校本科学生人数达 1000 余人 科研方面, 近年来主持 完成国家 863 计划项目 2 项 国家自然科学基金项目 70 余项 教育部科学技术研究重点项目 3 项 博士点基金项目 2 项 省科技计划项目 50 余项 在国内外重要学术刊物上发表了 1000 余篇高水平论文, 其中有 500 余篇论文, 其中 SCI/EI 收录 700 多篇, 在高教出版社 科学出版社等出版了 20 余部教材和专著, 获得省部级以上科研和教学成果奖 30 余项 经过多年的努力, 信息学院已经形成了数据与知识工程 并行与分布式计算 多媒体信息处理 计算机网络与数据通信 生物医学工程等特色研究方向 其中, 数据与知识工程 已成为了云南大学 云南省在电子信息领域内的优势学科方向, 是信息学院学科学位点的重要支撑 课题组于 2002 年和 2009 年先后两次获得了云南省自然科学一等奖, 是云南省该领域仅有的 2 个自然科学类一等奖 8

10 5. 云南大学及周边地图 云南大学校园 : 云南大学周边 : 9

11 6. 学生管理规章 (1) 学员入学时, 须持身份证 学生证或教师证等有效证件, 到云南大学宾馆大堂办理报到登记手续 (2) 学员应修完教学计划规定的学习内容 ( 含作业 实验 ), 综合考核考勤等, 合格者颁发 2012 年 VLDB 暑期学校结业证书 ; 学员结业时, 办理完宾馆退房等相关手续后, 方可离校 (3) 学员应按时签到 上课 下课, 不得出现无故旷课现象 ; 上课时注意仪表形象, 并保持良好的课堂秩序 (4) 妥善保管好自己的笔记本电脑 现金 信用卡 手机 首饰等贵重物品 ; 爱护宾馆和教室的公共设施 (5) 注意饮食安全和交通安全, 学员之间互相关照 ; 如发生意外事故, 及时向暑期学校通报, 因学员自身违法违章引发的事故, 由当事人自行当责 (6) 未经暑期学校负责人同意的情况下, 学员自行出游 参观等活动, 自行担责 10

12 7. 生活服务 购物 ( 市中心 ): 南屏步行街 金碧广场 ( 一二一大街师范大学站乘 84 路或 10 路到终点站下 ); 小西门 ( 一二一大街师范大学站乘 84 路 10 路或 65 路到百汇商场站下 ) 餐饮 ( 特色小吃 ): 文化巷 ( 云大西门外 ), 园西路 ( 云大东门外 ) 药店 : 健之佳药店 ( 云大西门对面 ) 医院 : 云南大学医院 ( 云大东门以北 ) 订票 : 华夏票务 ( 云大西门北面, 跨过一二一大街人行天桥 ; 电话 : ) 文印 : 九头鸟图文 ( 云大北门对面, 跨过一二一大街人行天桥, 再往东走 50 米 ) 公园 : 翠湖 ( 云大正门对面 ); 大观楼 ( 一二一大街师范大学站乘 22 路到终点站下 ); 金殿 ( 一二一大街师范大学站乘 10 路到终点站下 ); 民族村 ( 一二一大街师范大学站乘 64 路或 22 路到弥勒寺站下, 转乘 73 路到云南民族 村站下 ) 8. 旅游服务 云大宾馆旅游部 - 云南海外国际旅行社有限公司 电话 : , , 联系人 : 曾泓冰经理 11