京都大学教育研究振興財団助成事業
成 果 報 告 書
平成29年9月15日
公益財団法人京都大学教育研究振興財団会 長 辻
井 昭 雄 様助 成 の 種 類

所属部局・研究科

情報学研究科職 名・学 年

博士課程３年氏

ZHUANG CHENYI名

平成２９年度・国際研究集会発表助成
第26回人工知能国際会議

研 究 集 会 名

発 表 形 式□ 招 待

発 表 題 目

Understanding People Lifestyles: Construction of Urban Movement Knowledge
Graph from GPS Trajectory

開 催 場 所

Australia, Melbourne, The Melbourne Convention & Exhibition Centre

渡 航 期 間成 果 の 概 要

平成 29 年・□ 口 頭

8 月 18 日□ ポスター ・ □ その他（・～）

平成 29 年 8 月 26 日

タイトルは「成果の概要／報告者名」として、A４版２０００字程度・和文で作成し、添付して下さい。 「成果の概要」以外に添付する資料 □ 無□ 有()
交付を受けた助成金額

200,000 円

使 用 し た 助 成 金 額

200,000 円

返納すべき助成金額0円

会 計 報 告助 成 金 の 使 途 内 訳

延長ページ代31,195 円

学会参加費58,687 円

旅費110,118 円（今回の助成に対する感想、今後の助成に望むこと等お書き下さい。助成事業の参考にさせていただきます。）

当財団の助成についてI would like to thank for your subsidy, which was very convenient and efficient. Thesubsidy helped me to cover most of the cost during my travel to Australia. As a Ph.D.
student, an oral presentaion in a famous international conference is a valuable experience.
In the conference, I have met a lot of researchers from the Artificial Intelligence researcharea and exchanged novel ideas with them. Without your subsidy, it may be impossible forsuch a great opportunity.

成果の概要／Chenyi ZhuangThis time, I have attended the 26th International Joint Conference on Artificial Intelligence(IJCAI 2017). IJCAI is the main international gathering of researchers in Artificial Intelligence(AI) research area. IJCAI were held biennially in odd-numbered years since 1969. Starting with2016, since AI is becoming more and more popular, it will be held annually. This year, theconference was sponsored by more than 48 companies, organizations, and universities. Morethan 3,000 researchers from all around world came to attend this conference to share and discussstate-of-the-art research achievements. About the numbers of papers accepted by this conference,here is a brief statistics grouped by countries: China: 475; EU: 334; US: 255; Australia: 112;
Singapore: 64; Japan: 37; Rest: 126.
About my research work, in this conference, our team published a work about how to construct
an urban movement knowledge graph from GPS (Global Positioning System) trajectory data. By
analyzing the taxis’ GPS trajectories, we proposed a matrix factorization and neural network
based method to mine the underlying lifestyles in a city. In our experiments, I did find several
interesting lifestyles (moving patterns) in the city Beijing. The impacts of this work are two-fold:
the first one is that, from a theoretical point pf view, we proposed a strategy to ensemble thetotally different techniques: matrix factorization and neural network; on the other hand, as thesecond contribution, we constructed a knowledge graph of describing different moving patterns(i.e., lifestyles) in a city. The knowledge graph could be further utilized in the future work. For
example, it could be used to predict the traffic conditions in a city; it could be applied to simulate
the user mobilities in a city, and so on.
I have given an oral presentation in the morning (10:30 am – 12:00 am) on Aug. 24th. In the samemorning, I have also attended a poster session and presented our work in that session. During theoral presentation and the poster session, I have received a lot of questions, comments and evensome new ideas for further improvements. For example, Dr. Chang Xu asked a question about
how to improve the scalability of our algorithm to deal with a much bigger dataset. Our work
also attracted some attentions from the industry area. For example, the researchers from different
companies (e.g., IBM, Microsoft, DiDi, JingDong, and so on) were interested in our work.

In addition to my own presentation, I have also attended some other sessions that interested me.
For example, Prof. Stuart Russell from University of California, Berkeley has given a keynote
about “Provably Beneficial AI”. The main concern of this keynote is to pursue the benefits of AIand meanwhile to avoid the bad potential impacts that would bring by AI. Another talk is given
by Dr. Devi Parikh, a research scientist from Facebook AI Lab. She listed some open directionsin the research area of obtaining human-like consistency. Some sub-topics were mentioned in hertalk, like learning by playing, learning by asking, reasoning, and so on.
To make a conclusion, in this conference, I have published our team’s work and got a lot offeedbacks from the audiences. Meanwhile, I have listened to a lot of research achievement
reposts, which helped me to better understand the overview of the AI research area.
At last, I would like to thank “京都大学教育研究振興財団” again for your grant of “国際研究集会発表助成”. The grant covered most of my cost during my travel to Australia. I wish yourbusiness become further better in the future.