[dbjapan] 【参加募集】iDBワークショップ2010講演会（8月3日）【参加無料・どなたでも参加OKです！】

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

日本データベース学会の皆様：

お茶の水女子大学の渡辺です。

iDBワークショップ2010内で開催いたします講演会についてご案内させていただきます。
iDBワークショップ本体はクローズドな会ですが、講演会はどなたでもご自由に参加できます。
また参加費も無料です。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。

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                 iDBワークショップ2010講演会

          http://db-event.jpn.org/idb2010/invited-talks
 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
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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日にかけて神戸ファッションマートで開かれます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・情報学基礎研究
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.