学会員メーリングリストアーカイブ (2010年)

[dbjapan] 【参加募集】(訂正版) iDB2010ワークシ ョップ講演会【どなたで も参加OK!参加無料】

  • To: dbjapan [at] dbsj.org
  • Subject: [dbjapan] 【参加募集】(訂正版) iDB2010ワークシ ョップ講演会【どなたで も参加OK!参加無料】
  • From: Toshiyuki AMAGASA <amagasa [at] cs.tsukuba.ac.jp>
  • Date: Wed, 21 Jul 2010 23:30:30 +0900 (JST)

日本データベース学会の皆様

筑波大学の天笠です.度々失礼します.

先ほどお送りした参加募集ですが,一部誤って昨年の内容が入って
おりました.お詫びして訂正させていただきます.今年は青山学院
大学での開催ですので,どうぞお間違えのないようお気をつけくだ
さいますようお願い致します.

======================================================================
                 iDB2010ワークショップ講演会

  http://db-event.jpn.org/idb2010/index.php?route=invited-talks.html
  主催: 日本データベース学会,情報処理学会データベースシステム研究会
               電子情報通信学会データ工学研究会
======================================================================

日時: 2010年8月3日 13:00〜17:00 (iDBワークショップ2010内イベント)
会場: 青山学院大学 青山キャンパス 総研ビル(14号館) 12F 大会議室
   http://www.aoyama.ac.jp/other/map/aoyama.html
  住所: 〒150-8366 東京都渋谷区渋谷4-4-25
参加費: 無料
参加登録: 不要

8月2日から4日にかけて青山学院大学青山キャンパスで開かれますiDBワーク
ショップ2010にて,データベースおよびデータ工学分野で世界的に活躍されて
いる著名海外研究者による講演会を開催致します.参加登録,参加費は無料で
す.ぜひ奮ってご参加いただけますようよろしくお願い致します.

なお,8月4日には情報処理学会データベースシステム研究会・情報基礎とアク
セス技術研究会および電子情報通信学会データ工学研究会が開催されます.各
研究会への参加を予定されている皆様、ぜひこちらの講演にも参加をご検討く
ださい.

■講演会プログラム (13:00〜17:00)

1. TransDec: A Data-Driven Framework for Decision-Making in
Transportation System
 Prof. Cyrus Shahabi (University of Southern Colifornia)

2. A Unified Graph Model for Sentence-based Opinion Retrieval
 Prof. Kam-Fai Wong (The Chinese University of Hong Kong)

3. Architecture-Driven Modelling Methodologies with the following content
 Prof. Bernhard Thalheim

4. Networking the Asian WordNet on WordNet Management System (WNMS)
 Dr. Virach Sornlertlamvanich (NECTEC, Thailand)

5. Good Papers and Good Presentations
 Dr. Tetsuya Sakai (Microsoft Research Asia, China)

■講演概要

1. TransDec: A Data-Driven Framework for Decision-Making in
   Transportation System
   Prof. Cyrus Shahabi (University of Southern Colifornia)

   The vast amounts of transportation datasets (traffic flow,
   incidents, etc.)  collected by various federal and state agencies
   are extremely valuable in 1) real-time decision-making, planning,
   and management of the transportation systems, and 2) conducting
   research to develop new policies to enhance the efficacy of the
   transportation systems.  In this talk, I will present our
   data-driven framework, dubbed TransDec (short for Transportation
   Decision-Making), which enables real-time integration,
   visualization, querying, and analysis of dynamic and archived
   transportation data. I will show that considering the large size of
   the transportation data, variety of the data (different modalities
   and resolutions), and frequent changes of the data, implementation
   of such a scalable system that allows for effective querying and
   analysis of both archived and real-time data is an intrinsically
   challenging data management task. Subsequently, I will focus on a
   route-planning problem where the weights on the road-network edges
   vary as a function of time due to the variability of traffic
   congestion.  I will show that naive approaches to address this
   problem are either inaccurate or slow, motivating the need for new
   solutions.  Consequently, I will discuss our initial approach to
   this problem and demonstrate its implementation within the TransDec
   framework.


2. A Unified Graph Model for Sentence-based Opinion Retrieval
   Prof. Kam-Fai Wong (The Chinese University of Hong Kong)

   There is a growing research interest in opinion retrieval for
   on-line users’opinions are becoming more and more popular in
   business, social network, etc. Practically speaking, the goal of
   opinion retrieval is to retrieve documents, which entail opinions
   or comments, relevant to a target specified by the user's query. A
   fundamental challenge in opinion retrieval is information
   representation. Existing approaches are document-based and
   documents are represented by bag-of-word.  However, this
   representation cannot maintain the association between topic
   relevance and opinion relevance due to loss of contextual
   information.  For this reason, existing systems fail to capture the
   pairing information between an opinion and its corresponding
   target, and the relationship among opinions on an identical topic
   is often overlooked. This in turn seriously affects opinion
   retrieval performance.  In this paper, we propose a sentence-based
   opinion retrieval method.  We define word pairs to capture
   intra-sentence contextual information.  Additionally, we consider
   inter-sentence information to capture the relationships among the
   opinions on the same topic. Finally, two types of information are
   combined in a novel unified graph-based model, which can
   effectively rank the documents. Compared with existing approaches,
   experimental results on the COAE08 and COAE09 datasets show that
   our model has achieved significant improvement.

3. Architecture-Driven Modelling Methodologies with the following content
   Prof. Bernhard Thalheim

   Classical software development methodologies take architectural
   issues as granted or pre-determined. They thus neglect the impact
   decisions for architecture have within the development
   process. This omission is toleratable as long as we are considering
   monolithic systems. It cannot however been kept whenever we move to
   distributed systems. Web information systems pay far more attention
   to users support and thus require sophisticated layout and playout
   systems. These systems go beyond what has been known for
   presentation systems.  We thus discover that architecture plays a
   major role during systems analysis, design and development.  We
   thus target on building a framework that is based on early
   architectural decisions or on integration of new solutions into
   existing architectures. We aim at development of novel approaches
   to web information systems development that allow a co-evolution of
   architectures and software systems.

4. Networking the Asian WordNet on WordNet Management System (WNMS)
   Dr. Virach Sornlertlamvanich (NECTEC, Thailand)

   WordNet has been recognized as an important language resource of
   lexical semantic. Each sense of word is assigned a set of synonyms
   called synset which plays an important role in representing the
   meaning of the word.  Moreover, many other lexical semantic
   relations namely antonym, hypernym, hyponym, holonym, and meronym
   are provided to construct a large-scaled network of lexical
   semantic. The formalism of semantic representation in WordNet has a
   great advantage in terms of building a computation lexical
   database. Up to the present day, many approaches in information
   retrieval, query expansion, machine translation, word sense
   disambiguation, text classification and so on have shown the
   promising results in using WordNet to increase the performance. As
   a result, several efforts have been put to create WordNet for other
   languages. Asian WordNet (AWN) is one of the approaches to build
   the WordNet for Asian languages by translating and networking the
   synsets through the defined synset ID of Princeton WordNet.  To
   prepare an initial WordNet for a certain language, we assign the
   synset to a list of words from the existing bi-lingual dictionaries
   based on an assignment algorithm. The degree of confidence in the
   synset assignment has been proposed by computing the distance
   between a word to a member of a synset. Word synonyms are also used
   to serve in finding a candidate of synset.  As a result, the list
   of candidate synsets is proposed to a word entry together with a
   degree of confidence score. In our approach, we show the efficiency
   in nominating the synset candidate by using the most common lexical
   information. The algorithm is evaluated against the implementation
   of Thai-English, Indonesian-English, and Mongolian-English
   bi-lingual dictionaries. The experiment also shows the
   effectiveness of using the same type of dictionary from different
   sources. The results are then reviewed collaboratively online via
   http://www.asianwordnet.org/.  To exhibit a cross language access
   to the WordNet, we use the synset in the Princeton WordNet (PWN) as
   a key to retrieve a set of words in the target language. Moreover,
   the environment for developing the WordNet for Asian languages is
   designed in a distributed manner on the WordNet Management System
   (WNMS).  Each language may take care of the environment and share
   its own resulted WordNet through a common API of a web service
   protocol.  Currently, Asian WordNet (AWN) can serve some languages
   depending on the progress of the percentage of translation namely,
   Bengali (0.90%), Hindi (7.44%), Indonesian (27.58%), Japanese
   (30.35%), Korean (35.93%), Lao (33.05%), Mongolian (1.38%), Burmese
   (16.95%), Napali (0.03%), Sinhala (0.23%), Sundanese (0.06%), Thai
   (55.20%), and Vietnamese (10.43%). On the WNMS, not only to browse
   the WordNet of each language, the implementation in cross language
   WordNet and multilingual dictionary can be seen by configuration on
   the provided web API.

5. Good Papers and Good Presentations
   Dr. Tetsuya Sakai (Microsoft Research Asia, China)

   What makes a good research paper? What if your paper gets rejected?
   What makes a good presentation at a conference? I will share with
   you my experiences as an author, a Senior Program Committee member
   and a Best Paper Committee member of ACM SIGIR, so that you might
   want to answer these questions for yourself.