Discovery science : 4th international conference, DS 2001, Washington, DC, USA, November 25-28, 2001 : proceedings

510 Pages·2001·9.3 MB·English

by  International Conference on Discovery Science (4th : 2001 : Washington, D.C.)

L e c t u r e N o t e s i n A r t i f i c i a l I n t e l l i g e n c e 2 2 2 6
S u b s e r i e s o f L e c t u r e N o t e s i n C o m p u t e r S c i e n c e
E d i t e d b y J . G . C a r b o n e l l a n d J . S i e k m a n n
L e c t u r e N o t e s i n C o m p u t e r S c i e n c e
E d i t e d b y G . G o o s , J . H a r t m a n i s , a n d J . v a n L e e u w e n
3
B e r lin
H e id e lb e r g
N e w Y o r k
B a r c e lo n a
H o n g K o n g
L o n d o n
M ila n
P a r is
T o k y o
K l a u s P . J a n t k e A y u m i S h i n o h a r a ( E d s . )
D i s c o v e r y S c i e n c e
4 t h I n t e r n a t i o n a l C o n f e r e n c e , D S 2 0 0 1
W a s h i n g t o n , D C , U S A , N o v e m b e r 2 5 - 2 8 , 2 0 0 1
P r o c e e d i n g s
1 3
S e r ie s E d ito r s
J a im e G . C a r b o n e ll, C a r n e g ie M e llo n U n iv e r s ity , P itts b u rg h , P A , U S A
J o¨ rg S ie k m a n n , U n iv e r s ity o f S a a r la n d , S a a r b r u¨ c k e n , G e r m a n y
V o lu m e E d ito r s
K la u s P . J a n tk e
D F K I G m b H S a a r b r u¨ c k e n
6 6 1 2 3 S a a r b r u¨ c k e n , G e r m a n y
E - m a il: ja n tk e @ d f k i.d e
A y u m i S h in o h a r a
K y u s h u U n iv e r s ity , D e p a r tm e n t o f I n f o r m a tic s
6 - 1 0 - 1 H a k o z a k i, H ig a s h i- k u , F u k u o k a 8 1 2 - 8 5 8 1 , J a p a n
E - m a il: a y u m i@ i.k y u s h u - u .a c .jp
C a ta lo g in g - in - P u b lic a tio n D a ta a p p lie d f o r
D ie D e u ts c h e B ib lio th e k - C I P - E in h e its a u f n a h m e
D is c o v e r y s c ie n c e : 4 th in te r n a tio n a l c o n f e r e n c e ; p r o c e e d in g s / D S 2 0 0 1 ,
W a s h in g to n , D C , U S A , N o v e m b e r 2 5 - 2 8 , 2 0 0 1 . K la u s P . J a n tk e ; A y u m i
S h in o h a r a ( e d .) . - B e r lin ; H e id e lb e rg ; N e w Y o r k ; B a r c e lo n a ; H o n g K o n g ;
L o n d o n ; M ila n ; P a r is ; T o k y o : S p r in g e r, 2 0 0 1
( L e c tu r e n o te s in c o m p u te r s c ie n c e ; V o l. 2 2 2 6 : L e c tu r e n o te s in
a r tifi c ia l in te llig e n c e )
I S B N 3 - 5 4 0 - 4 2 9 5 6 - 5
C R S u b je c t C la s s ifi c a tio n ( 1 9 9 8 ) : I .2 , H .2 .8 , H .3 , J .1 , J .2
I S B N 3 - 5 4 0 - 4 2 9 5 6 - 5 S p r in g e r- V e r la g B e r lin H e id e lb e rg N e w Y o r k
T h is w o rk is su b je c t to c o p y rig h t. A ll rig h ts a re re se rv e d , w h e th e r th e w h o le o r p a rt o f th e m a te ria l is
c o n c e rn e d , sp e c ifi c a lly th e rig h ts o f tra n sla tio n , re p rin tin g , re -u se o f illu stra tio n s, re c ita tio n , b ro a d c a stin g ,
re p ro d u c tio n o n m ic ro fi lm s o r in a n y o th e r w a y , a n d sto ra g e in d a ta b a n k s. D u p lic a tio n o f th is p u b lic a tio n
o r p a rts th e re o f is p e rm itte d o n ly u n d e r th e p ro v isio n s o f th e G e rm a n C o p y rig h t L a w o f S e p te m b e r 9 , 1 9 6 5 ,
in its c u rre n t v e rsio n , a n d p e rm issio n fo r u se m u st a lw a y s b e o b ta in e d fro m S p rin g e r-V e rla g . V io la tio n s a re
lia b le fo r p ro se c u tio n u n d e r th e G e rm a n C o p y rig h t L a w .
S p rin g e r-V e rla g B e rlin H e id e lb e rg N e w Y o rk
a m e m b e r o f B e rte lsm a n n S p rin g e r S c ie n c e + B u sin e ss M e d ia G m b H
h ttp ://w w w .sp rin g e r.d e
© S p rin g e r-V e rla g B e rlin H e id e lb e rg 2 0 0 1
P rin te d in G e rm a n y
T y p e se ttin g : C a m e ra -re a d y b y a u th o r
P rin te d o n a c id -fre e p a p e r S P IN : 1 0 8 4 0 9 7 3 0 6 /3 1 4 2 5 4 3 2 1 0

V I P re fa c e

Table of Contents
Invited Papers
The Discovery Science Project in Japan............................... 1
Setsuo Arikawa
Discovering Mechanisms: A Computational Philosophy of
Science Perspective................................................. 3
Lindley Darden
Queries Revisited .................................................. 16
Dana Angluin
InventingDiscoveryTools:CombiningInformationVisualizationwithData
Mining ........................................................... 17
Ben Shneiderman
Robot Baby 2001 .................................................. 29
Paul R. Cohen, Tim Oates, Niall Adams, and Carole R. Beal
Regular Papers
VML: A View Modeling Language for Computational Knowledge Discovery 30
Hideo Bannai, Yoshinori Tamada, Osamu Maruyama, and
Satoru Miyano
Computational Discovery of Communicable Knowledge: Symposium Report 45
Saˇso Dˇzeroski and Pat Langley
Bounding Negative Information in Frequent Sets Algorithms ............ 50
I. Fortes, J.L. Balca´zar, and R. Morales
Functional Trees ................................................... 59
Jo˜ao Gama
Spherical Horses and Shared Toothbrushes: Lessons Learned from a
Workshop on Scientific and Technological Thinking..................... 74
Michael E. Gorman, Alexandra Kincannon, and
Matthew M. Mehalik
Clipping and Analyzing News Using Machine Learning Techniques ....... 87
Hans Gru¨ndel, Tino Naphtali, Christian Wiech, Jan-Marian Gluba,
Maiken Rohdenburg, and Tobias Scheffer
Towards Discovery of Deep and Wide First-Order Structures:
A Case Study in the Domain of Mutagenicity.......................... 100
Tama´s Horv´ath and Stefan Wrobel
X Table of Contents
Eliminating Useless Parts in Semi-structured Documents Using
Alternation Counts................................................. 113
Daisuke Ikeda, Yasuhiro Yamada, and Sachio Hirokawa
Multicriterially Best Explanations.................................... 128
Naresh S. Iyer and John R. Josephson
Constructing Approximate Informative Basis of Association Rules........ 141
Kouta Kanda, Makoto Haraguchi, and Yoshiaki Okubo
Passage-Based Document Retrieval as a Tool for Text Mining with User’s
Information Needs ................................................. 155
Koichi Kise, Markus Junker, Andreas Dengel, and
Keinosuke Matsumoto
Automated Formulation of Reactions and Pathways in
Nuclear Astrophysics: New Results ................................... 170
Sakir Kocabas
An Integrated Framework for Extended Discovery in Particle Physics..... 182
Sakir Kocabas and Pat Langley
Stimulating Discovery .............................................. 196
Ronald N. Kostoff
Assisting Model-Discovery in Neuroendocrinology ...................... 214
Ashesh Mahidadia and Paul Compton
A General Theory of Deduction, Induction, and Learning ............... 228
Eric Martin, Arun Sharma, and Frank Stephan
Learning Conformation Rules........................................ 243
Osamu Maruyama, Takayoshi Shoudai, Emiko Furuichi,
Satoru Kuhara, and Satoru Miyano
Knowledge Navigation on Visualizing Complementary Documents........ 258
Naohiro Matsumura, Yukio Ohsawa, and Mitsuru Ishizuka
KeyWorld: Extracting Keywords from a Document as a Small World ..... 271
Yutaka Matsuo, Yukio Ohsawa, and Mitsuru Ishizuka
A Method for Discovering Purified Web Communities .................. 282
Tsuyoshi Murata
Divide and Conquer Machine Learning for a Genomics Analogy Problem.. 290
Ming Ouyang, John Case, and Joan Burnside