讲座：Cross-lingual Entity Linking for Web Tables
题 目: Cross-lingual Entity Linking for Web Tables
嘉 宾: ZHU Qili（Kenny）, Professor, Shanghai Jiao Tong University
主持人: 宋颖达 博士，安泰经济与管理学院管理科学系
地 点：上海交通大学徐汇校区 包图A303室
This talk studies the problem of linking string mentions from web tables in one language to the corresponding named entities in a knowledge base written in another language, which we call the cross-lingual table linking task. We present a joint statistical model to simultaneously link all mentions that appear in one table. The framework is based on neural networks, aiming to bridge the language gap by vector space transformation and a coherence feature that captures the correlations between entities in one table. Experimental results report that our approach improves the accuracy of cross-lingual table linking by a relative gain of 12.1%. Detailed analysis of our approach also shows a positive and important gain brought by the joint learning framework and the coherence feature.
Kenny Qili Zhu is a Professor of computer science at Shanghai Jiao Tong University. He graduated with B.Eng (Hons) in Electrical Engineering in 1999 and PhD in Computer Science in 2005 from National University of Singapore. He was a postdoctoral researcher and lecturer from 2007 to 2009 at Princeton University. Prior to that, he was a software design engineer at Microsoft, Redmond, WA. From Feb 2010 to Aug 2010, he was a visiting professor at Microsoft Research Asia in Beijing. Kenny's main research interests are knowledge engineering, artificial intelligence and programming language. He has published extensively in AI, database and programming languages at top venues such as SIGMOD, KDD, IJCAI, AAAI, CIKM, ICDE, POPL, and ICFP. He has served on the PC of WWW, CIKM, ECML, COLING, SAC, WAIM, APLAS and NDBC, etc. His research has been supported by NSF China, MOE China, Microsoft, Google, Oracle, Morgan Stanley and AstraZeneca. Kenny is the winner of the 2013 Google Faculty Research Award and 2014 DASFAA Best Paper Award.