Fourth Workshop on

Learning with Logics and Logics for Learning

(LLLL, L4)

June 5 and/or 6

Collocated with the 20th Annual Conference of the Japanese Scociety for Artificial Intelligence (June 7-9, 2006)

The announcement of other collocated workshops is here.
The LLLL homepage is here.

The workshop program is here.

The LLLL 06 workshop was held with success.   We would like to express our thankfulness to the invited speakers, Prof. Gyorgy Turan and Prof. Tamas Horvath,
all PC members, and all speakers and audiences.

Scope of the workshop :

    Logic is a fundamental and useful representation method in Artificial Intelligence. In the area of Machine Learning, various types of computational logic, such as logic programs, first-order logic, description logic, higher-order logic, have been used for representing knowledge obtained with various types of learning mechanisms including identification in the limit, PAC learning, on-line learning, EXACT learning, machine discovery, and learning based on Bayesian networks. On the other hand, machine learning procedures are used in giving semantics to logic and foundations of some procedures in mathematics.
    This workshop is proposed to bring together researchers who are interested in both of the areas of machine learning and computational logic, and to have intensive discussions on various relations between the two with making their interchange more active.

Potential (but not exclusive) topics include :

 Learning and knowledge discovery using logics
                Algorithmic aspects of learning based on logics
                Logics for machine learning and knowledge discovery
                Logics using machine learning
                Machine learning as a foundation of mathematics/mathematical procedures
                Amalgamation of logic-based learning and statistical/information theoretical learning
                Learning and knowledge discovery from relational data
                Learning and knowledge discovery from structured/semi-structured data
                Learning and knowledge discovery from real-valued data

Deadline of (first) paper submission: Extended !!! March 25, 2006

Notification of Acceptance: April 10, 2006
Deadline of camera ready submission: April 21, 2006
Workshop date: June 5 (Monday) and/or 6 (Tuesday), 2006
Workshop site: Tower Hall Funabori, Edogawa, Tokyo JAPAN

Paper format: Submitted papers should consist of the maximum of 7 pages with the LaTeX style file available (downloaded here), and be formatted in the PDF format.
How to submit: Authors are invited to submit thier papers through the EasyChair system. 
For submission please press the this button.
Now Closed !!!

The working note (proceedings) will be published by JSAI for the workshop, and some outstanding papers will be published in a post proceedings book as Lecture Notes in Artificial Intelligence from Springer, with such papers from other collocated workshops.

Workshop organizers : Akihiro Yamamoto (Kyoto University)  
Kouichi Hirata (Kyushu Institute of Technology)
Ken Satoh (National Institute of Informatics)

Program Committee : Yoji Akama (Tohoku University, Japan)
                                   Marta Arias (Columbia University, USA)
                                   Hiroki Arimura (Hokkaido University, Japan)
                                   Kouichi Hirata (Kyushu Institute of Technology, Japan)
                                   Eiju Hirowatari(The University of Kitakyushu, Japan)
                                   Tamas Horvath (Fraunhofer Institute, Germany)
                                   Katsumi Inoue (National Institute of Informatics, Japan)
                                   Roni Khardon (Tufts University, USA)
                                   Eric Martin (University of New South Wales, Australia)
                                   Shin-ichi Minato
(Hokkaido University, Japan)
                                   Tetsuhiro Miyahara (Hiroshima City University, Japan)
                                   Luc de Raedt (University of Freiburg, Germany)
                                   M.R.K. Krishna Rao (King Fahd University of Petroleum and Minerals, Saudi Arabia)
                                   Taisuke Sato (
Tokyo Institute of Technology, Japan)
                                   Ken Satoh (National Institute of Informatics, Japan)
                                   Joe Suzuki (Osaka University, Japan)
                                   Gyorgy Turan (University of Illinois at Chicago, USA)
                                   Hiroaki Watanabe(Imperial College London, UK)
                                   Akihiro Yamamoto (Kyoto University, Japan)

Workshop Program:

June 5th (Monday)
13:00-13:10    Opening

Invited Talk (1)
13:10-14:10    Remarks on Learning and Commonsense Reasoning
                     Gyorgy Turan   

14:10-14:30    Coffee break

Session 1: Logical Foundations of Inductive Inference
14:30-15:00    Polynomial Time Inductive Inference of Interval Graph Pattern Languages from Positive Data
                     Hitoshi Yamasaki and Takayoshi Shoudai   
15:00-15:30    Inferability of Closed Set Systems From Positive Data
                     Matthew de Brecht, Masanori Kobayashi, Hiroo Tokunaga and Akihiro Yamamoto
15:30-15:50    Consistency Conditions of Inductive Inference of Functions
                      Yohji Akama

15:50-16:10    Coffee break

Session 2: Learning with Logical Formulae
16:10-16:40    Subsumption Algorithm for Chordal Clauses
                     Megumi Kuwabara, Kouichi Hirata and Masateru Harao   
16:40-17:10    Learning from Real-Valued Data with the Model Inference Mechanism through the Gray-Code Embedding
                     Mahito Sugiyama, Eiju Hirowatari, Hideki Tsuiki and Akihiro Yamamoto

18:00-20:00   Workshop dinner

June 6th (Tuesday)
Invited Talk (2)
9:30- 10:30    Mining and Learning from Graph Structured Data
                    Tamas Horvath   

10:30-10:50    Coffee break

Session 4: Knowledge Discovery from Structured Data
10:50-11:20    An Extended Branch and Bound Search Algorithm for Finding Top-N Formal Concepts of Documents
                     Makoto Haraguchi and Yoshiaki Okubo   
11:20-11:40    Table Recognition Using Attribute Likelihood Computed from Words
                     Tsubasa Kitayama, Kazutaka Shimada and Tsutomu Endo   
11:40-12:10    Extraction of Frequent Causal Episodes from Bacterial Culture Data
                     Takashi Katoh, Kouichi Hirata and Masateru Harao   

12:10-13:30    Lunch
Session 5: N-gram Analysis
13:30-14:00    N-gram Analysis Based on Zero-suppressed BDDs
                     Ryutaro Kurai, Shin-ichi Minato and Thomas Zeugmann   
14:00-14:30    The Gram Distribution for Rooted Ordered Trees
                     Nobuhito Ohkura, Kouichi Hirata, Tetsuji Kuboyama, Masateru Harao and Shin-Ichi Nakano   
14:30-15:00    A q-Gram based Distance Measure for Ordered Labeled Trees
                     Tetsuji Kuboyama, Kouichi Hirata, Nobuhito Ohkura and Masateru Harao   

15:00-15:10    Closing

Workshop  Dinner
The  time  and  date : 18:00|20:00C5th June
Place : gHorai-no-mahin the confernce site (Tower Hall Funabori)
FeeF 8,000 JPY
Please fill the form at the registration desk if you join the dinner.

          Postal addess :   Akihiro Yamamoto
                                                Graduate School of Informatics
                                                Kyoto University

                                                Yoshida-Honmachi, Sakyo-ku, Kyoto

                                                606-8501 JAPAN

        Email : akihiro (at) /* Please replace (at) with @ */ 
                       Phone: +81 75 753 5995
                       Fax: +81 75 753 5628