Latest advances in inductive logic programming
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[2015]
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| 650 | 4 | |a Induction (Logic) | |
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Datensatz im Suchindex
| _version_ | 1819708045042647040 |
|---|---|
| adam_text | LATEST ADVANCES IN
INDUCTIVE LOGIC PROGRAMMING
This book represents a selection of papers presented at the Inductive Logic Programming (ILP) workshop held at Cumberland Lodge, Great Windsor Park. The collection marks two decades since the first ILP workshop in 1991. During this period the area has developed into the main forum for work on logic-based machine learning. The chapters cover a wide variety of topics, ranging from theory and ILP implementations to state-of-the-art applications in real-world domains. The international contributors represent leaders in the field from prestigious institutions in Europe, North America and Asia.
Graduate students and researchers in this field will find this book highly useful as it provides an up-to-date insight into the key sub-areas of implementation and theory of ILP. For academics and researchers in the field of artificial intelligence and natural sciences, the book demonstrates how ILP is being used in areas as diverse as the learning of game strategies, robotics, natural language understanding, query search, drug design and protein modelling.
Contents
R
Preface v
Acknowledgments vii
Part 1: Applications 1
1. Can ILP Learn Complete and Correct Game Strategies? 3
Stephen H. Muggleton and Changze Xu
1.1 Introduction........................................... 3
1.2 ILP Representation of Games............................ 4
1.3 Experiments............................................ 5
1.4 Related Work, Conclusions and Future Work.............. 9
Bibliography............................................... 10
2. Induction in Nonmonotonic Causal Theories
for a Domestic Service Robot 11
Jianmin Ji and Xiaoping Chen
2.1 Introduction.......................................... 11
2.2 Nonmonotonic Causal Theories.......................... 12
2.3 Induction in Causal Theories.......................... 13
2.4 A Case Study in a Domestic Service Robot’s Domain . . 14
2.5 Discussion and Conclusion............................. 17
Bibliography............................................... 18
3. Using Ontologies in Semantic Data Mining with g-SEGS
and Aleph 19
Anze Vavpetic and Nada Lavrac
3.1 Introduction.......................................... 19
3.2 Related Work.......................................... 20
ix
X
Latest Advances in Inductive Logic Programming
3.3 g-SEGS................................................ 21
3.4 Problem Formulation in Aleph ......................... 22
3.5 Experimental Results.................................. 23
3.6 Conclusion............................................ 25
Acknowledgments........................................... 25
Bibliography............................................... 25
4. Improving Search Engine Query Expansion Techniques
with ILP 27
José Carlos Almeida Santos and Manuel Fonseca de Sam Bento Ribeiro
4.1 Introduction and Motivation........................... 27
4.2 Experiments........................................... 29
4.3 Conclusions and Future Work........................... 33
Acknowledgments............................................ 34
Bibliography............................................... 34
5. ILP for Cosmetic Product Selection 35
Hiroyuki Nishiyama and Fumio Mizoguchi
5.1 Introduction.......................................... 35
5.2 Previous Cosmetics Recommendation Service Using the
Smartphone............................................ 37
5.3 Design and Implementation of Diagnosis System
by Smartphone......................................... 39
5.4 Conclusion............................................ 41
Bibliography............................................ 41
6. Learning User Behaviours in Real Mobile Domains 43
Andreas Markitanis, Domenico Corapi,
Alessandra Russo and Emil C. Lupu
6.1 Introduction.......................................... 43
6.2 Background............................................ 45
6.3 Towards an Adaptive System Using ILP.................. 46
6.4 Real Mobile-Domain Applications....................... 48
6.5 Conclusion........................................... 50
Bibliography............................................... 50
Contents xi
7. Discovering Ligands for TRP Ion Channels Using
Formal Concept Analysis 53
Mahito Sugiyama, Kentaro Imago, Keisuke Otaki and Akihiro Yamamoto
7.1 Introduction........................................... 53
7.2 Methods................................................ 55
7.3 Results and Discussion.............................. 58
Acknowledgments............................................... 59
Bibliography.................................................. 59
8. Predictive Learning in Two-Way Datasets 61
Beau Piccart, Hendrik Blocked, Andy Georges and Lieven Eeckhout
8.1 Situating Two-Way Learning........................... 61
8.2 The Effects of Transposition........................... 64
8.3 Applications........................................... 65
8.4 Conclusions............................................ 67
Acknowledgment................................................ 67
Bibliography.................................................. 68
9. Model of Double-Strand Break of DNA in Logic-Based
Hypothesis Finding 69
Barthélémy Dworkin, Andrei Doncescu,
Jean-Charles Faye and Katsumi Inoue
9.1 Introduction........................................... 69
9.2 Double-Strand Break of DNA............................. 70
9.3 Ampliative Reasoning in Biological Systems............. 71
9.4 Logical Model of a Double-Strand Break................. 72
9.5 Results................................................ 73
9.6 Conclusion............................................. 76
Bibliography.................................................. 76
Part 2: Probabilistic Logical Learning 77
10. The PITA System for Logical-Probabilistic Inference 79
Fabrizio Riguzzi and Terrance Swift
79
80
81
83
85
87
ST-
BS
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105
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109
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Latest Advances in Inductive Logic Programming
10.1 Introduction................................
10.2 Probabilistic Logic Programming.............
10.3 The PITA System ............................
10.4 Experiments.................................
Bibliography......................................
Learning a Generative Failure-Free PRISM Clause Waleed Alsanie and James Cussens
11.1 Introduction ...............................
11.2 Scoring with Variational Free Energy........
11.3 Building and Searching the Hypothesis Space .
11.4 Experiment..................................
11.5 Conclusion and Future Work .................
Bibliography......................................
Statistical Relational Learning of Object Affordances for Robotic Manipulation
Bogdan Moldovan, Martijn van Otterlo, Plinio Moreno, José Santos-Victor and Luc De Raedt
12.1 Introduction................................
12.2 Affordance-Based Models ....................
12.3 Learning Relational Skills and Experiments . .
12.4 ProbLog Modeling and Results................
12.5 Conclusion and Future Work .................
Acknowledgments...................................
Bibliography......................................
Learning from Linked Data by Markov Logic Man Zhu and Zhiqiang Gao
13.1 Introduction................................
13.2 Description Logic ACC.......................
13.3 Learning from Linked Data...................
13.4 Experiments.................................
13.5 Conclusion and Remarks......................
Acknowledgment....................................
Bibliography......................................
Contents
xm
14. Satisfiability Machines 113
Filip Zelezny
14.1 Introduction.......................................... 113
14.2 Probabilistic Model................................... 114
14.3 Comparing Pm(c) and Ps(c) ............................ 115
14.4 Discriminative Learning............................... 118
14.5 Conclusion............................................ 119
Acknowledgment............................................. 119
Bibliography............................................... 119
Part 3: Implementations 121
15. Customisable Multi-Processor Acceleration of Inductive
Logic Programming 123
Andreas K. Fidjeland, Wayne Luk and Stephen H. Muggleton
15.1 Introduction.......................................... 123
15.2 Background: Sequential and Parallel ILP............... 124
15.3 The Arvand Processor.................................. 127
15.4 Multi-Processor Architecture for ILP.................. 132
15.5 Multi-Processor Architecture Generation............... 134
15.6 Results............................................... 135
15.7 Concluding Remarks.................................... 139
Acknowledgments............................................ 139
Bibliography............................................... 139
16. Multivalue Learning in ILP 143
Orlando Muoz Texzocotetla and Ren Mac Kinney Romero
16.1 Introduction.......................................... 143
16.2 Uni value Clauses..................................... 145
16.3 Multivalue Clauses.................................... 146
16.4 Experiments........................................... 148
16.5 Conclusions and Future Work .......................... 149
Bibliography............................................... 150
xiv Latest Advances in Inductive Logic Programming
17. Learning Dependent-Concepts in ILP: Application to
Model-Driven Data Warehouses 151
Moez Essaidi, Aomar Osmani and Celine Rouveirol
17.1 Overview ........................................... 151
17.2 Background Definitions ............................. 153
17.3 Relational Learning of Dependent-Concept............ 156
17.4 Empirical Results................................... 160
17.5 Conclusion.......................................... 169
Bibliography............................................. 169
18. Graph Contraction Pattern Matching for Graphs
of Bounded Treewidth 173
Takashi Yamada and Takayoshi Shoudai
18.1 Introduction........................................ 173
18.2 Preliminaries....................................... 175
18.3 A Pattern Matching Algorithm for GC-Patterns .... 177
Bibliography.............................................. 180
19. mLynx: Relational Mutual Information 181
Nicola Di Mauro, Teresa M.A. Basile, Stefano Ferilli and Floriana Esposito
19.1 Introduction........................................ 181
19.2 Feature Construction and Classification............. 182
19.3 Mutual Information Feature Selection................ 184
19.4 Experiments......................................... 186
Bibliography.............................................. 188
Part 4: Theory 189
20. Machine Learning Coalgebraic Proofs 191
Ekaterina Komendantskaya
20.1 Background.......................................... 191
20.2 Methodology......................................... 193
20.3 Agenda and Preliminary Results ..................... 195
Bibliography.............................................. 197
Contents
xv
21. Can ILP Deal with Incomplete and Vague
Structured Knowledge? 199
Francesca A. Lisi and Umberto Straccia
21.1 Introduction........................................ 199
21.2 Fuzzy Description Logics............................ 200
21.3 ILP for Learning Fuzzy DL Inclusion Axioms.......... 202
21.4 Final Remarks ...................................... 205
Bibliography............................................. 205
Part 5: Logical Learning 207
22. Towards Efficient Higher-Order Logic Learning
in a First-Order Datalog Framework 209
Niels Pahlavi and Stephen H. Muggleton
22.1 Introduction........................................ 209
22.2 HOLL with First-Order Datalog and Progol............ 211
22.3 Experiments......................................... 213
22.4 Conclusion and Further Work......................... 215
Bibliography.............................................. 215
23. Automatic Invention of Functional Abstractions 217
Robert J. Henderson and Stephen H. Muggleton
23.1 Introduction........................................ 217
23.2 KANDINSKY’s Abstraction Invention Algorithm .... 218
23.3 Experiment.......................................... 222
23.4 Related/Further Work and Conclusion................. 223
Acknowledgments........................................... 224
Bibliography............................................. 224
Part 6: Constraints 225
24. Using Machine-Generated Soft Constraints
for Roster Problems 227
Yoshihisa Shiina and Hayato Ohwada
24.1 Introduction........................................ 227
24.2 A Simple Roster Problem............................. 228
XVI
Latest Advances in Inductive Logic Programming
24.3 Proposed Method..................................... 230
24.4 Experiment.......................................... 232
24.5 Concluding Remarks.................................. 233
Bibliography.............................................. 233
Part 7: Spacial and Temporal
25. Relational Learning for Football-Related Predictions Jan Van Haaren and Guy Van den Broeck
25.1 Introduction .............................
25.2 Related Work..............................
25.3 Current Limitations and Challenges .......
25.4 Relational Representation.................
25.5 Learning Tasks............................
25.6 Learning Example..........................
25.7 Conclusion................................
Acknowledgments.................................
Bibliography....................................
237
237
238
239
240
241 241 243 243 243
Index
245
|
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| author2 | Muggleton, Stephen H. 1959- Watanabe, Hiroaki Richard 1968- |
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| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Conference Proceeding Book |
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| genre_facet | Konferenzschrift 2011 Cumberland Lodge, Windsor, UK |
| id | DE-604.BV042911633 |
| illustrated | Illustrated |
| indexdate | 2024-12-24T04:36:25Z |
| institution | BVB |
| institution_GND | (DE-588)1026226325 |
| isbn | 9781783265084 |
| language | English |
| lccn | 014033096 |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-028339412 |
| oclc_num | 918763153 |
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| owner | DE-703 DE-11 |
| owner_facet | DE-703 DE-11 |
| physical | xvi, 247 Seiten Illustrationen, Diagramme (teilweise farbig) |
| publishDate | 2015 |
| publishDateSearch | 2015 |
| publishDateSort | 2015 |
| publisher | Imperial College Press |
| record_format | marc |
| spellingShingle | Latest advances in inductive logic programming Logic programming Induction (Logic) Machine learning Induktion (DE-588)4026765-9 gnd Programmierung (DE-588)4076370-5 gnd Induktive logische Programmierung (DE-588)4807625-9 gnd |
| subject_GND | (DE-588)4026765-9 (DE-588)4076370-5 (DE-588)4807625-9 (DE-588)1071861417 |
| title | Latest advances in inductive logic programming |
| title_auth | Latest advances in inductive logic programming |
| title_exact_search | Latest advances in inductive logic programming |
| title_full | Latest advances in inductive logic programming Stephen H. Muggleton & Hiroaki Watanabe, Imperial College London, UK |
| title_fullStr | Latest advances in inductive logic programming Stephen H. Muggleton & Hiroaki Watanabe, Imperial College London, UK |
| title_full_unstemmed | Latest advances in inductive logic programming Stephen H. Muggleton & Hiroaki Watanabe, Imperial College London, UK |
| title_short | Latest advances in inductive logic programming |
| title_sort | latest advances in inductive logic programming |
| topic | Logic programming Induction (Logic) Machine learning Induktion (DE-588)4026765-9 gnd Programmierung (DE-588)4076370-5 gnd Induktive logische Programmierung (DE-588)4807625-9 gnd |
| topic_facet | Logic programming Induction (Logic) Machine learning Induktion Programmierung Induktive logische Programmierung Konferenzschrift 2011 Cumberland Lodge, Windsor, UK |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028339412&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028339412&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT ilpwindsor latestadvancesininductivelogicprogramming AT muggletonstephenh latestadvancesininductivelogicprogramming AT watanabehiroakirichard latestadvancesininductivelogicprogramming |