DBSJ & ACM SIGMODJ 講演会(12月16日）のご案内

[Miyuki Nakano <miyuki [at] tkl.iis.u-tokyo.ac.jp>]

dbjapanの皆様、

12月16日に下記の講演会がございます。
奮ってご参加ください。

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　☆☆☆　　Dr. Xuemin Lin　講演会のご案内　　　☆☆☆

共催　日本データベース学会
　　　ACM SIGMOD日本支部

日時　１２月１６日（土）　午後５時半〜午後６時半
場所　東京大学生産技術研究所　E棟 5F 会議室A(Ew-501)
      E棟　5階　エレベータをあがって左手奥
      http://www.iis.u-tokyo.ac.jp/map/index.html

      (ご注意）
　　　当日は日曜日ですので、正門からしか入れません。マップをご確認の
　　　上、お入りください。また、ビルの入り口が施錠されております。
　　　当日、Ｅ棟入り口に案内を出しておきますので、内線電話にて
　　　ご連絡ください。

Title: Selecting Stars: The k Most Representative Skyline Operator
Speaker: Xuemin Lin, School of Computer Science & Engineering
             University of New South Wales, Australia

参加費　無料

参加ご希望の方は、
　日本データベース学会のホームページにて
　　　( http://www.dbsj.org/ )
　　　会員登録の後（会費無料、すでに登録されている方は結構です）、
      sigmodj_lecture [at] tkl.iis.u-tokyo.ac.jpに
　　　添付の参加申込書をお送り下さい。

皆様のご参加をお待ちしております。

                        日本データベース学会　副会長・企画委員長
                        （ACM　SIGMOD日本支部　支部長）　北川博之

　　　　　　　　　　　　　　　　　　　　　　 担当委員　　中野　美由紀
　　　　　　　　　　
                        連絡(問合せ)先　日本データベース学会、ACM SIGMOD
日本支部
                                sigmodj_lecture [at] tkl.iis.u-tokyo.ac.jp
　　　　　　　　　　　　　　　　http://www.dbsj.org/


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To: sigmodj_lecture [at] tkl.iis.u-tokyo.ac.jp

日本データベース学会・ACM SIGMOD日本支部共催　講演会　参加申し込み

１２月１６日（土）の講演会に参加
・名前　　　
・ご所属
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Title: Selecting Stars: The k Most Representative Skyline Operator
Speaker: Xuemin Lin, School of Computer Science & Engineering
             University of New South Wales, Australia

Abstract

Skyline computation has many applications including multi-criteria decision
making. In this talk, we investigate the problem of selecting k
skyline points so that the number of points, which are dominated by at least
one of these k skyline points, is maximized.
We first present an efficient dynamic programming based exact
algorithm in a 2d-space.
Then, we show that the problem is NP-hard when the dimensionality
is $3$ or more and it can be approximately solved by a polynomial time
algorithm with the guaranteed approximation ratio 1 - 1/e.
To speed-up the computation, an efficient, scalable, index-based
randomized algorithm is developed by applying a probabilistic
counting technique.
A comprehensive performance evaluation demonstrates that our
randomized technique is very efficient, highly accurate, and scalable.

(Joint work with Yidong Yuan, Qing Zhang, and Ying Zhang)

Short bio

Xuemin Lin is an Associate Professor (reader) in the School of Computer
Science and Engineering, the University of New South Wales. He has been
the head of database research group since 2001. Before joining UNSW,
Xuemin held various academic positions at University of Queensland and
University of Western Australia. He also taught at the Chinese
University of Hong Kong in 2000. Dr. Lin got his PhD in Computer Science
from the University of Queensland in 1992 and his BSc in Applied Math
from Fudan University in 1984. During 1984-1988, he studied for PhD in
Applied Math at Fudan University.

His current research interests lie in data streams, approximate query
processing, data streams, spatial data analysis, and graph visualization.
He has published about 100 research papers in theory and DB societies
including TODS, TKDE, Algorithmic, Theoretical Computer Science, VLDB,
ICDE, EDBT, etc. Xuemin serves as PC (or PC-co chairs) in
a number of conferences in database systems and algorithms.
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中野　美由紀		東京大学　生産技術研究所　喜連川研究室
Miyuki NAKANO		Institute of Industrial Science, Univ. of Tokyo
miyuki [at] tkl.iis.u-tokyo.ac.jp