报告题目：Geotagging Tweets to Foursquare
报告日期及时间：2016年06月06日周一09：30
报告地点：B403
报告人： 孙爱欣 副教授
报告人单位： 新加坡南洋理工大学
报告人简介：
Dr. SUN Aixin is an Associate Professor with School of Computer Science and Engineering (SCSE), Nanyang Technological University (NTU), Singapore. He received B.A.Sc (1st class honours) and Ph.D. both in Computer Engineering from the same school in 2001 and 2004 respectively. Aixin's research areas include Text Mining, Social Computing, Multimedia, and Digital Libraries. Many of his papers appear in major international conferences including SIGIR, CIKM, WSDM, ACM Multimedia, and journals lik TKDE, JASIST, and IP&M. Aixin has been a PC member of many major conferences including SIGIR, KDD, WWW, and reviewer for many IEEE/ACM transactions and Journals.
报告摘要：
Many users casually reveal their locations such as restaurants, landmarks, and shops in their tweets. Recognizing such fine-grained locations from tweets and then linking the location mentions to well-defined location profiles (e.g., with formal name, detailed address, and geo-coordinates etc.) offer a tremendous opportunity for many studies and applications. Using the location profiles sourced from Foursquare, we recognize the location mentions in tweets and then link each mention to its corresponding location profile, to geotag the tweets. We propose a novel joint framework to perform location recognition and location linking simultaneously in a joint search space. More specifically, we formulate this end-to-end location linking problem as a structured prediction problem and propose a beam-search based algorithm. Based on the concept of multi-view learning, we further enable the algorithm learning from unlabeled data. Experiment results show that the proposed joint learning algorithm outperforms the state-of-the-art solutions, and learning from unlabeled data improves both the recognition and linking accuracy.
邀请人： 李晨亮 副教授
