[dbjapan] 【明日です】iDB2010ワークショップ講演会【どなたでも参加可】

[Chiemi Watanabe <chiemi [at] is.ocha.ac.jp>]

データベース学会の皆様

お茶大の渡辺です。
iDB2010ワークショップ講演会が明日に迫りましたので、
最終案内をさせていただきます。
是非ふるってご参加いただきますよう、よろしくお願いいたします。

======================================================================
                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.htmlcol
 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 California)

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
 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 California)

  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
  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.