Context Mediation Among Knowledge Discovery Components

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Universal-Publishers, 2004 - Language Arts & Disciplines - 216 pages
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Context Mediation is a field of research that is concerned with the interchange of information across different environments, which provides a vehicle to bridge semantic gaps among disparate entities. Knowledge Discovery is concerned with the extraction of actionable information from large databases. A challenge that has received relatively little attention is knowledge discovery in a highly disparate environment, that is multiple heterogeneous data sources, multiple domain knowledge sources and multiple knowledge patterns. This thesis tackles the problem of semantic interoperability among data, domain knowledge and knowledge patterns in a knowledge discovery process using context mediation. All presented techniques, methods and models are applied in real-world scenarios, covering disciplines from a wide range of industry, namely web mining and marketing, manufacturing, meteorology and internationalisation. When feasible, industry standards were utilised, for instance ODMG, PMML and KQML. The carried out research has resulted in almost fifty international publications, including the co-authorship of a book, a journal editorship and one conference best paper award.
 

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Contents

MOTIVATION
1
Introduction
2
12 What is Within the Scope of the Thesis
4
13 and What is Beyond
5
14 Outline of Thesis
6
143 Context Mediation in Knowledge Discovery
7
145 Appendices
8
16 Summary
9
532 Context and Mediator Declaration
85
54 Context Object Query Language
86
55 An Internationalisation Application
87
551 Definition of Locales and Locale Mediators
88
552 Definition of Localised Data
90
553 Working with Localised Data
91
56 Recapitulation
92
Contextual Domain Knowledge Mediation
93

Related Work
11
21 A Historical Perspective of Semantic Heterogeneity
12
22 Organisation of Literature Review
13
23 Semantic Heterogeneity Resolution in MultiDatabases
15
232 Materialised View Integration
17
233 Summary and Evaluation of discussed Approaches
19
242 Mediationbased Data Models and Query Languages
21
243 Summary and Evaluation of discussed Approaches
23
25 Contexts in Database Environments
24
251 Context Representation and Interchange
25
252 Context Coordination and Building
28
253 Contextdriven Data Manipulation
29
255 Summary and Evaluation of discussed Approaches
30
26 Semantic Similarity and Proximity
31
262 Contextbased Approaches
32
263 Summary and Evaluation of discussed Approaches
34
271 Knowledge Discovery from Multiple Information Sources
35
272 Information Fusion and Ensemble Methods
36
273 Knowledge Comparison
38
274 Summary and Evaluation of discussed Approaches
39
CONTEXTS AND CONTEXT MEDIATION
42
Context Fundamentals
43
312 Cognitive Science and Psychology
44
314 Artificial Intelligence
45
3143 Context in Reasoning
46
3144 Context in Machine Learning
47
315 Miscellaneous Fields of Study
48
32 Some Principles of the Study of Contexts
49
33 The Concept of Contexts
50
332 Contextual Comparison Operations
52
334 Ordering Semantic Values
54
3343 Abstract Data Types
55
335 Distances between Semantic Values
56
336 Topological Organisation of Contexts
57
34 InterOntology Relationships
60
35 Recapitulation
62
Context Mediation
63
42 A Primitive Data Context Mediator
64
43 Early Prototypical Work
65
432 Performance and Scalability
68
44 A Product and Data Management Application
69
441 The Collaboration Architecture
70
442 Product and Data Management Ontologies
72
443 Ontology Mappings and Mediation
74
444 Communication in Product and Data Management
76
45 Recapitulation
77
CONTEXT MEDIATION IN KNOWLEDGE DISCOVERY
78
Contextual Data Mediation
79
52 The Context Object Data Model
80
522 The ODMG Object Model
81
523 ODMG MetaModel Extensions
82
53 Context Object Definition Language
84
62 Domain Knowledge Classification
94
622 Constraints
96
63 Domain Knowledge in Context
97
632 Contextual Domain Knowledge
98
633 Domain Knowledge Context Mediation
100
64 An Application in the Meteorology Domain16
101
641 Some Meteorological Background Information
102
642 Domain Knowledge Extraction and Mediation
105
6421 Domain Knowledge for Data PreProcessing
106
6422 Domain Knowledge for Pattern Discovery
112
643 Summary of Domain Knowledge Mediation
115
65 Summary of Proposed Concepts
116
Contextual Knowledge Pattern Mediation
117
72 Knowledge Pattern Framework
118
73 Contextual Ranking of Knowledge Patterns
122
731 Quantitative and Qualitative Measurements
123
7311 Normalisation
125
7313 Quantitative Measurement
126
7314 Measurement Coalescence
127
732 Manipulating m Distributions
129
7321 Boosting
130
7323 Inversion
131
7324 Concatenation of Manipulations
132
74 Comparison of Discovered Knowledge
133
742 Comparative Operations
134
7431 Segments
135
7432 Associations
136
75 Knowledge Cumulus
138
76 A Web Mining Application
140
762 Knowledge Ranking in different Contexts
142
77 Summary of Presented Techniques
143
CONCLUSIONS
145
Concluding Remarks
146
812 Mapping of Context Concepts to Knowledge Discovery Components
147
813 Applying Context Mediation Facilities in different Domains
148
814 A Contextual Knowledge Discovery Architecture
149
82 Future Work
150
822 Enhancements to Presented Research
152
83 Coda
154
Appendices
156
A1 Collection of Introduced Definitions
157
A12 Data Mediation
161
A14 Knowledge Pattern Mediation
162
A2 Full BNF of Contextual ODMG Extensions
164
A3 Predictive Modeling Markup Language
166
A4 List of Relevant Publications
169
A42 Refereed Journal Articles
170
A44 Refereed Workshop and Colloquia Papers
172
A45 Miscellaneous Publications
174
A5 References
176
Copyright

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Page 183 - H. Garcia-Molina, Y. Papakonstantinou, D. Quass, A. Rajaraman, Y. Sagiv, J. Ullman, and J. Widom. The TSIMMIS Approach to Mediation: Data Models and Languages.
Page xiii - Attention is drawn to the fact that the copyright of this thesis rests with its author. This copy of the thesis has been supplied on condition that anyone who consults it is understood to recognise that its copyright rests with its author and that no quotation from the thesis and no information derived from it may be published without the author's prior written consent.
Page 197 - Generating Data Integration Mediators that Use Materialization,

About the author (2004)

Alex Buchner is the co-founder and technical lead of Synergy Learning, the UK's largest Moodle partner. He has been involved in system and database administration for two decades and has been administering virtual learning environments of all shapes and sizes since their advent on the educational landscape. Alex holds a PhD in Computer Science and an MSc in Software Engineering. He has authored over 50 international publications, including two books, and is a frequent speaker on Moodle and related open-source technologies.

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