Conceptual Structures in Practice

426 Pages·2009·4.312 MB·English

by  Pascal Hitzler, Henrik Scharfe

CONCEPTUAL
STRUCTURES
IN PRACTICE
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Chapman & Hall/CRC
Studies in Informatics Series
SEriES EDiTor
G. Q. Zhang
Case Western Reserve University
Department of EECS
Cleveland, Ohio, U.S.A
PubliSHED TiTlES
Stochastic Relations: Foundations for Markov Transition Systems
Ernst-Erich Doberkat
Conceptual Structures in Practice
Pascal Hitzler and Henrik Schärfe
Context-Aware Computing and Self-Managing Systems
Waltenegus Dargie
C6062_FM.indd 2 4/3/09 4:06:41 PM
Chapman & Hall/CRC
Studies in Informatics Series
CONCEPTUAL
STRUCTURES
IN PRACTICE
Edited by
Pascal Hitzler
Henrik Schärfe
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The following figures were provided by Springer -Verlag, Berlin:
Figure 13.4. (Schärfe, Henrik; Hitzler, Pascal; Ohrstrom, Peter [Eds.] Conceptual Structures: Inspiration and
Application. 14th International Conference on Conceptual Structures, July 16-21, 2006, p. 292. Used with
permission.)
Figure 13.5. (Schärfe, Henrik; Hitzler, Pascal; Ohrstrom, Peter [Eds.] Conceptual Structures: Inspiration and
Application. 14th International Conference on Conceptual Structures, July 16-21, 2006, p. 298. Used with
permission.)
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Library of Congress Cataloging‑in‑Publication Data
Conceptual structures in practice / editors, Pascal Hitzler and Henrik Schärfe. -- 1st ed.
p. cm. -- (Chapman & Hall/CRC studies in informatics series ; 2)
Includes bibliographical references and index.
ISBN 978-1-4200-6062-1 (alk. paper)
1. Conceptual structures (Information theory) 2. Knowledge representation
(Information theory) I. Hitzler, Pascal. II. Schärfe, Henrik.
Q387.2.C68 2009
003’.54--dc22 2008036234
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Contents
Preface ix
Acknowledgments xiii
About the Editors xv
Contributors xvii
I Introductions 1
1 A Brief Introduction to Formal Concept Analysis 3
Markus Krötzsch and Bernhard Ganter
1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2 Contexts and Concepts . . . . . . . . . . . . . . . . . . . . . 4
1.3 From Contexts to Concept Lattices . . . . . . . . . . . . . . 7
1.4 The Logic of Attributes . . . . . . . . . . . . . . . . . . . . . 10
1.5 Attribute Exploration . . . . . . . . . . . . . . . . . . . . . . 12
1.6 Summary and Outlook . . . . . . . . . . . . . . . . . . . . . 14
2 Formal Logic with Conceptual Graphs 17
Frithjof Dau
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.2 Short Introduction to Conceptual Graphs . . . . . . . . . . . 18
2.3 Conceptual Graphs from a Formal Point of View . . . . . . . 23
2.4 The General Approach for Formal Logic with CGs . . . . . . 28
2.5 Different Forms of Conceptual Graphs . . . . . . . . . . . . . 34
2.6 Further Literature . . . . . . . . . . . . . . . . . . . . . . . . 43
II Tools 45
3 Software Tools for Formal Concept Analysis 47
Peter Becker and Joachim Hereth Correia
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
3.2 The ConExp Concept Explorer . . . . . . . . . . . . . . . . 48
3.3 ConImp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
3.4 The ToscanaJ Suite . . . . . . . . . . . . . . . . . . . . . . 56
3.5 Docco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
3.6 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . 70
v
vi Contents
3.7 Student Projects . . . . . . . . . . . . . . . . . . . . . . . . . 71
4 Efficient Computation with Conceptual Graphs 73
Galia Angelova
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
4.2 Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
4.3 Constructionof CompactFSA-Based Encoding of the Knowl-
edge Base . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
4.4 Experimental Assessment of Conceptual Data Compression . 93
4.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
4.6 Student Projects . . . . . . . . . . . . . . . . . . . . . . . . . 98
III Foundations 99
5 Conceptual Graphs for Representing Conceptual Structures 101
John F. Sowa
5.1 Representing Conceptual Structures . . . . . . . . . . . . . . 102
5.2 Towarda Natural Logic . . . . . . . . . . . . . . . . . . . . . 107
5.3 A Moving Picture of Thought . . . . . . . . . . . . . . . . . 111
5.4 Representing Natural Language Semantics . . . . . . . . . . 118
5.5 Ongoing Research . . . . . . . . . . . . . . . . . . . . . . . . 123
5.6 Appendix: The Common Logic Standard . . . . . . . . . . . 126
6 Formal Concept Analysis and Contextual Logic 137
Rudolf Wille
6.1 The Birth of Formal Concept Analysis. . . . . . . . . . . . . 137
6.2 The Mathematics of Formal Concept Analysis . . . . . . . . 143
6.3 Applications of Formal Concept Analysis . . . . . . . . . . . 153
6.4 Contextual Concept Logic . . . . . . . . . . . . . . . . . . . 161
6.5 Contextual Judgment Logic . . . . . . . . . . . . . . . . . . . 166
IV Text Analysis 175
7 Linguistic Data Exploration 177
Uta Priss
7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
7.2 Modeling Semantic Relations . . . . . . . . . . . . . . . . . . 179
7.3 Deriving Lattices from Lexical Databases and Corpora . . . 185
7.4 Student Projects . . . . . . . . . . . . . . . . . . . . . . . . . 196
8 Ontology Learning Using Corpus-Derived Formal Contexts 199
Philipp Cimiano
8.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 199
8.2 FCA for Ontology Learning from Text. . . . . . . . . . . . . 202
8.3 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . 217
8.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219
Contents vii
8.5 Student Projects . . . . . . . . . . . . . . . . . . . . . . . . . 221
V Web Semantics 223
9 A Lexico-Logical Approach to Ontology Engineering 225
Sebastian Rudolph and Johanna Völker
9.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 225
9.2 Preliminaries . . . . . . . . . . . . . . . . . . . . . . . . . . . 226
9.3 Lexical and Logical Knowledge Acquisition . . . . . . . . . . 227
9.4 Relational Exploration . . . . . . . . . . . . . . . . . . . . . 232
9.5 An Integrated Approach to Ontology Refinement. . . . . . . 233
9.6 Implementation and Example. . . . . . . . . . . . . . . . . . 236
9.7 Conclusion and Outlook . . . . . . . . . . . . . . . . . . . . . 241
9.8 Student Projects . . . . . . . . . . . . . . . . . . . . . . . . . 243
10 Faceted Document Navigation 245
Jon Ducrou and Peter Eklund
10.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 245
10.2 The Email Domain and Formal Concept Analysis:
MailSleuth . . . . . . . . . . . . . . . . . . . . . . . . . . . 246
10.3 Navigating Images Using FCA: ImageSleuth . . . . . . . . 261
10.4 Conclusion and Summary . . . . . . . . . . . . . . . . . . . . 270
10.5 Student Projects . . . . . . . . . . . . . . . . . . . . . . . . . 271
11 Optimizing Social Software System Design 273
Aldo de Moor
11.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 273
11.2 Social Software: From Tools to Systems . . . . . . . . . . . . 274
11.3 A Conceptual Model of Functionality Matching in Collabora-
tive Communities . . . . . . . . . . . . . . . . . . . . . . . . 281
11.4 The Functionality Matching Process . . . . . . . . . . . . . . 285
11.5 Discussion and Conclusion . . . . . . . . . . . . . . . . . . . 291
11.6 Student Projects . . . . . . . . . . . . . . . . . . . . . . . . . 292
VI Intelligent Systems 295
12 Semantic Annotations and Localization of Resources 297
Michel Chein
12.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 297
12.2 An Annotation Language . . . . . . . . . . . . . . . . . . . . 302
12.3 Construction of Annotations . . . . . . . . . . . . . . . . . . 309
12.4 Search Methods . . . . . . . . . . . . . . . . . . . . . . . . . 313
12.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 316
12.6 Student Projects . . . . . . . . . . . . . . . . . . . . . . . . . 318
viii Contents
13 An Overview of Amine 321
Adil Kabbaj
13.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 321
13.2 Amine Architecture . . . . . . . . . . . . . . . . . . . . . . . 322
13.3 Ontology and KB Layers . . . . . . . . . . . . . . . . . . . . 325
13.4 Algebraic Layer . . . . . . . . . . . . . . . . . . . . . . . . . 330
13.5 Memory-BasedInference and Learning Strategies Layer . . . 332
13.6 Programming Layer . . . . . . . . . . . . . . . . . . . . . . . 334
13.7 Multi-Agents Layer . . . . . . . . . . . . . . . . . . . . . . . 338
13.8 Amine as an IDE for Symbolic Programming . . . . . . . . . 338
13.9 AmineasanIDEforIntelligentSystemProgramming: Natural
Language Processing with Prolog+CG as an Example . . . . 339
13.10 Amine as an IDE for Intelligent Agents Programming and
Multi-Agents Systems (MAS) . . . . . . . . . . . . . . . . . . 343
13.11 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . 344
13.12 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . 345
13.13 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 346
13.14 Student Projects . . . . . . . . . . . . . . . . . . . . . . . . . 347
14 Active Knowledge Systems 349
Harry S. Delugach
14.1 What Is an Active Knowledge System? . . . . . . . . . . . . 350
14.2 Grounding a Knowledge Model . . . . . . . . . . . . . . . . . 353
14.3 Applications of Active Knowledge Systems . . . . . . . . . . 359
14.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 368
14.5 Student Projects . . . . . . . . . . . . . . . . . . . . . . . . . 368
References 371
Index 401
Preface
This book is about structures: Conceptual Structures. Following standard
definitions, we may tentatively define a structure as consisting of elements
of something, and relations connecting those elements. And so it becomes
obvious that structures are ubiquitous; they occur everywhere in nature and
in culture. In fact, it is hard to think of anything that is not – some way or
another – arranged in structures. In this sense, if one is to study structure,
the whole world may become his laboratory, and going through the chap-
ters of this book, we easily see that the examples and illustrations given by
the authors range considerably. Here, however, we are not just interested in
structures. Weseekoutandinvestigateaspecialkindofstructure,namelythe
conceptualones. A conceptmay be consideredas a basic element ofthought,
as opposed to an element of perception. Conceptual Structures, therefore, is
the name of a field ofresearchthatinvestigatesvariousaspects ofthoughtby
means of structures. The scientific community of Conceptual Structures goes
backmorethan20yearsandhasbroughttogetherawidearrayofresearchers
from mathematics, computer science, linguistics, social sciences, and philos-
ophy to ponder the nature and implications of Conceptual Structures. This
diversity in approaches and legacies of thought has become a hallmark of the
community, and the very reason that many researchers return to the annual
conferences year after year. The workshop proceedings from the early years
(1986–1992)and the conference proceedings published by Springer in the es-
teemed Lecture Notes on Artificial Intelligence series (1993–current) form a
valuablearchiveoverprogressanddevelopmentinthiscommunity. Addition-
ally, a number of important books on specific topics within the scope of the
community have been published. But until now, we have not had a book
thatsurveystheentiretyofthe field. Conceptual Structures in Practice is the
remedyforthat,anditisourhopethatthebookwillserveasabenchmarkof
researchinConceptualStructuresaswellasanimportantsourceofinspiration
for students and researchers within this and related fields of scholarly effort.
Guidedbyfundamentalresearchquestionssuchaschartingouttheinternal
structureofaconcept(Wille,Chapter6),andthequestionofhowtorepresent
age-old knowledge about knowing (Sowa, Chapter 5), Conceptual Structures
in Practice takesusthroughthebasicbutnon-trivialtaskofestablishingcon-
ceptual relations such as [T]−relation→[T] or the seemingly simplistic struc-
ture of a cross-table as the foundation for research that now reaches into the
cuttingedgeofleadingtechnologyinknowledgerepresentationandknowledge
mining.
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