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Understanding Semantics-Based Decision Support [Kõva köide]

(National Institute of Technology, Haryana)
  • Formaat: Hardback, 140 pages, kõrgus x laius: 234x156 mm, kaal: 453 g, 6 Tables, black and white; 24 Illustrations, black and white
  • Ilmumisaeg: 26-Nov-2020
  • Kirjastus: Chapman & Hall/CRC
  • ISBN-10: 0367443139
  • ISBN-13: 9780367443139
Teised raamatud teemal:
Understanding Semantics-Based Decision SupportSuurem pilt
  • Formaat: Hardback, 140 pages, kõrgus x laius: 234x156 mm, kaal: 453 g, 6 Tables, black and white; 24 Illustrations, black and white
  • Ilmumisaeg: 26-Nov-2020
  • Kirjastus: Chapman & Hall/CRC
  • ISBN-10: 0367443139
  • ISBN-13: 9780367443139
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780367443139.html
Märksõnad:

This book is an attempt to establish in the readers the importance of creating interoperable data stores and writing rules for handling this data. It also covers extracts from a few project dissertations and a research funded project that the author had supervised.• Describes the power of ontologies for better data management• Provides an overview of knowledge engineering including ontology engineering, tools and techniques• Provides sample development procedures for creating two domain ontologies.• Depicts the utility of ontological representation in situation awareness• Demonstrates recommendation engine for unconventional emergencies using a hybrid reasoning approach.• The text explains how to make better utilization of resources when emergency strikesGraduates and undergraduates doing courses in artificial intelligence, semantic web and knowledge engineering will find this book beneficial.

Foreword ix
Preface xiii
About the Author xvii
Acknowledgment xix
Acronyms and Abbreviations xxi
1 Semantics-based Decision Support - An Introduction
1(20)
1.1 Decision Support
1(2)
1.2 Situation Awareness
3(1)
1.3 Paradigm Shift from Data to Knowledge
4(1)
1.4 Intelligence and Semantics
5(3)
1.4.1 Understanding Semantics
5(1)
1.4.2 Semantic Intelligence
6(2)
1.5 Intersection of STs and DSS
8(1)
1.6 Sample Use Cases
9(4)
1.6.1 E-Government
10(1)
1.6.2 Healthcare
10(1)
1.6.3 Understanding Natural Language
10(1)
1.6.4 IT Service
11(1)
1.6.5 Tourism
11(1)
1.6.6 Oil and Gas Industry
11(1)
1.6.7 Education
11(1)
1.6.8 Medicine
12(1)
1.6.9 Customer Service
12(1)
1.6.10 NASA
12(1)
1.6.11 Law
12(1)
1.6.12 News
12(1)
1.6.13 Big Fish in the Market
13(1)
1.7 Case Study
13(8)
1.7.1 Unconventional Emergencies
13(1)
1.7.2 The State of the Art
13(2)
1.7.3 Managerial Implications (Benefits)
15(1)
1.7.3.1 Government
15(1)
1.7.3.2 Military Personnel
15(1)
1.7.3.3 Society
16(5)
2 Semantic Technologies as Enabler
21(36)
2.1 Data Models
21(3)
2.1.1 Data Models for Structured Data
23(1)
2.1.2 Data Models for Semi-Structured and Unstructured Data
23(1)
2.2 Representing Semantics
24(1)
2.3 Representative Semantic Data Models
25(3)
2.3.1 Semantic HTML
26(1)
2.3.2 Using Web (2.0) APIs
27(1)
2.3.3 Publishing Linked Data
27(1)
2.4 Semantic Technologies
28(9)
2.4.1 Foundations
28(1)
2.4.2 The Data Model (RDF)
29(1)
2.4.3 Ontology
30(1)
2.4.3.1 Ontology Development
31(1)
2.4.3.2 Ontology Evaluation
32(1)
2.4.4 Knowledge Description Languages
32(1)
2.4.4.1 RDF Schema
33(1)
2.4.4.2 Web Ontology Language
34(1)
2.4.4.3 Simple Knowledge Organization System
34(1)
2.4.5 Serializations (Syntax/Formats)
35(1)
2.4.6 Manipulating RDF Data
36(1)
2.5 RDF Data Access and Management
37(5)
2.5.1 RDF Data Storage
37(2)
2.5.2 Query Processing
39(1)
2.5.2.1 Adding, Deleting, and Exporting Data
40(1)
2.5.3 inference/Reasoning
41(1)
2.5.3.1 Ontology Reasoning
41(1)
2.5.3.2 Rule-Based Reasoning
42(1)
2.6 Rules and Rule Languages
42(3)
2.6.1 Kinds of Rules
42(1)
2.6.2 Rule Languages
43(2)
2.6.2.1 Discussion
45(1)
2.7 Semantic Tools
45(12)
2.7.1 Ontology Development Environments
45(1)
2.7.2 RDF-izers
46(1)
2.7.3 Application Programming Interfaces
46(1)
2.7.3.1 Apache Jena
46(1)
2.7.3.2 Eclipse RDF4J (Formerly OpenRDF Sesame)
47(1)
2.7.3.3 Redland C Libraries
48(1)
2.7.3.4 OWL API
48(1)
2.7.3.5 Sparta
49(1)
2.7.3.6 Protege-OWL API
49(1)
2.7.4 Semantic Repository and Reasoner
49(2)
2.7.5 Semantic Reasoner
51(2)
2.7.6 Ontology Visualization
53(4)
3 Semantics-Based Decision Support for Unconventional Emergencies
57(10)
3.1 The Problem
57(1)
3.2 The Solution
58(3)
3.3 Tools and Techniques
61(6)
4 Knowledge Representation and Storage
67(22)
4.1 Developing Knowledge Stores
67(1)
4.2 Developing Ontologies
68(8)
4.2.1 Defining Ontology
68(4)
4.2.2 Methodology
72(1)
4.2.2.1 Scope Determination
72(2)
4.2.2.2 Concept Identification
74(1)
4.2.2.3 Concept Analysis and Organization
74(1)
4.2.2.4 Encoding
74(1)
4.2.2.5 Evaluation
74(1)
4.2.3 SupOnt-EO
74(2)
4.3 Evaluation of Ontologies
76(7)
4.3.1 Evaluation by Verification
77(1)
4.3.1.1 Metric-Based Evaluation
78(2)
4.3.1.2 Criteria-Based Evaluation
80(1)
4.3.1.3 Cost-Based Evaluation
80(2)
4.3.2 Evaluation by Validation
82(1)
4.3.2.1 Semantic Layer
82(1)
4.3.2.2 Application Layer
83(1)
4.4 Archiving Past Experiences (Case Base)
83(1)
4.5 Acquiring Expertise (Rule Base)
84(5)
5 Situation Awareness
89(12)
5.1 System Architecture
89(2)
5.2 Knowledge Base Browser
91(3)
5.2.1 Visualization
91(1)
5.2.2 Search
92(2)
5.3 Question Answering
94(7)
5.3.1 Predefined Queries
95(3)
5.3.2 Custom Queries
98(3)
6 Advisory System
101(16)
6.1 Conceptual Model
101(3)
6.1.1 Algorithmic Overview
103(1)
6.2 Case-Based Reasoning
104(1)
6.2.1 Representation and Storage of Cases
104(1)
6.2.2 CBR Life Cycle
104(1)
6.3 Augmenting CBR with Semantic Technologies
105(3)
6.3.1 Life Cycle of Ontology-Based CBR
106(2)
6.4 Augmenting CBR with Decision Trees
108(4)
6.4.1 Incremental CBR
108(2)
6.4.2 Selecting the Most Distinctive Feature
110(2)
6.5 Augmenting CBR with Rules
112(1)
6.6 Ongoing Case Study
112(5)
6.6.1 Action Recommendation in Earthquake
113(4)
7 Multilingual and Multimodal Access
117(14)
7.1 Motivation
117(2)
7.1.1 Benefits of Multilingual and Multimodal Access
119(1)
7.2 Multilingual Knowledge Representation
119(6)
7.2.1 Integration of Linguistic Constructs
119(2)
7.2.2 Ontology Mediation
121(2)
7.2.3 Globalization
123(2)
7.3 Multilingual Keyword Search
125(2)
7.3.1 Demonstration of Multilingual Search in Hindi
125(1)
7.3.2 Demonstration of Multilingual Search in Punjabi
126(1)
7.4 Multimedia Semantic Integration and Resource Access
127(4)
7.4.1 Multimedia Ontology Construction
128(1)
7.4.2 Multimedia Visualization
129(1)
7.4.3 Multimedia Search
129(2)
8 Concluding Remarks and Outlook for the Future
131(2)
Index 133
Dr. Sarika Jain graduated from Jawaharlal Nehru University (India) in 2001. Her doctorate, awarded in 2011, is in the field of knowledge representation in Artificial Intelligence. She has served in the field of education for over 19 years and is currently in service at the National Institute of Technology, Kurukshetra (Institute of National Importance), India. Dr. Jain has authored or co-authored over 100 publications including books. Her current research interests are knowledge management and analytics, the semantic web, ontological engineering, and intelligent systems. She is currently working toward solving the interoperability problem generated by initiative in the internet of things, big data, and cloud computing.

Dr. Jain has supervised two doctoral scholars (five ongoing) who are now pursuing their postdoctoral studies, one in Spain and the other in Germany. Currently, she is guiding 15 students for their masters and doctoral research work in the area of knowledge representation. She serves as a reviewer for journals published by IEEE, Elsevier, and Springer. She has been involved as a program- and steering-committee member at many prestigious conferences in India and abroad. She has two funded research projects: one ongoing, funded by CSIR TEQIP- III and worth Rs 2.58 lakhs, and the other completed, funded by the Defense Research and Development Organization, India, and worth Rs 40 lakhs. She applied for a patent in November 2019. Dr. Jain has held various administrative positions at the department and institute level in her career, like head of department, hostel warden, faculty in charge of technical and cultural fests, member of research degree committee, and Center Incharge Examinations.

Dr. Jain has visited the United Kingdom and Singapore to present her research work. She has continuously supervised DAAD interns from different universities of Germany and many interns from India every summer. She works in collaboration with various researchers across the globe, including in Germany, Austria, Australia, Malaysia, the USA, and Romania. She has organized various challenges, conferences, and workshops, including the

National Information Technology Conference (NITC), the Global Initiative of Academic Networks (GIAN) by the Ministry of Human Resource Development, Government of India, the International Conference on Smart Computing and Communication (ICSCC), the International Conference on Advanced Communication and Computational Technology (ICACCT), and International Conference on Eco-Friendly Computing and Communication Systems. She is a member of the Institute of Electrical and Electronics Engineers (IEEE) and the Association for Computing Machinery (ACM) and a Life Member of the Computer Society of India (CSI), the International Association of Engineers (IAENG), and the International Association of Computer Science and Information Technology (IACSIT).

Dr. Jain is highly interested in worldwide collaborations and is seeking scholars and interns for her research group. For more and most updated information, see https://sites.google.com/view/nitkkrsarikajain/.