Introduction to E-Librarian Services / 1: |
From Ancient to Digital Libraries / 1.1: |
From Searching to Finding / 1.2: |
Searching the Web / 1.2.1: |
Searching Multimedia Knowledge Bases / 1.2.2: |
Exploratory Search / 1.2.3: |
E-Librarian Services / 1.3: |
Overview / 1.3.1: |
Early Question-Answering Systems / 1.3.2: |
Natural Language Interface / 1.3.3: |
No Library without a Librarian / 1.3.4: |
Characteristics of an E-Librarian Service / 1.3.5: |
Overview and Organization of the Book / 1.4: |
Key Technologies of E-Librarian Services / Part I: |
Semantic Web and Ontologies / 2: |
What is the Semantic Web? / 2.1: |
The Vision of the Semantic Web / 2.1.1: |
Semantic Web vs. Web N.O / 2.1.2: |
Three Principles Ruling the Semantic Web / 2.1.3: |
Architecture / 2.1.4: |
Ontologies / 2.2: |
Ontology Structure / 2.2.1: |
Upper and Domain Ontologies / 2.2.2: |
Linked Data / 2.2.3: |
Expressivity of Ontologies / 2.2.4: |
XML Extensible Markup Language / 2.3: |
XML: Elements, Attributes and Values / 2.3.1: |
Namespaces and Qualified Names / 2.3.2: |
XML Schema / 2.3.3: |
Complete Example / 2.3.4: |
Limitations of XML / 2.3.5: |
RDF-Resource Description Framework / 2.4: |
RDF Triples and Serialization / 2.4.1: |
RDF Schema / 2.4.2: |
Limitations of RDF / 2.4.3: |
Owl 1 and Owl 2 - Web Ontology Language / 2.5: |
Instances, Classes and Restrictions in Owl / 2.5.1: |
From Owl 1 to Owl 2 / 2.5.2: |
Sparql, the Query Language / 2.5.4: |
Description Logics and Reasoning / 3: |
DL- Description Logics / 3.1: |
Concept Descriptions / 3.1.1: |
DL Languages / 3.1.2: |
Equivalences between OWL and DL / 3.1.3: |
DL Knowledge Base / 3.2: |
Terminologies (TBox) / 3.2.1: |
World Descriptions (ABox) / 3.2.2: |
Interpretations / 3.3: |
Interpreting Individuals, Concepts, and Roles / 3.3.1: |
Modeling the Real World / 3.3.2: |
Inferences / 3.4: |
Standard Inferences / 3.4.1: |
Non-Standard Inferences / 3.4.2: |
Natural Language Processing / 4: |
Overview and Challenges / 4.1: |
Syntax, Semantics and Pragmatics / 4.1.1: |
Difficulties of NLP / 4.1.2: |
Zipf's law / 4.1.3: |
Dealing with Single Words / 4.2: |
Tokenization and Tagging / 4.2.1: |
Morphology / 4.2.2: |
Building Words over an Alphabet / 4.2.3: |
Operations over Words / 4.2.4: |
Semantic Knowledge Sources / 4.3: |
Semantic relations / 4.3.1: |
Semantic resources / 4.3.2: |
Dealing with Sentences / 4.4: |
Phrase Types / 4.4.1: |
Phrase Structure / 4.4.2: |
Grammar / 4.4.3: |
Formal languages / 4.4.4: |
Phrase structure ambiguities / 4.4.5: |
Alternative parsing techniques / 4.4.6: |
Multi-Language / 4.5: |
Semantic Interpretation / 4.6: |
Information Retrieval / 5: |
Retrieval Process / 5.1: |
Document Indexation and Weighting / 5.2: |
Index of terms / 5.2.1: |
Weighting / 5.2.2: |
Retrieval Models / 5.3: |
Boolean Model / 5.3.1: |
Vector Model / 5.3.2: |
Probabilistic Model / 5.3.3: |
Page Rank / 5.3.4: |
Semantic Distance / 5.3.5: |
Other Models / 5.3.6: |
Retrieval Evaluation / 5.4: |
Precision, Recall, and Accuracy / 5.4.1: |
Design and Utilization of E-Librarian Services / Part II: |
Ontological Approach / 6: |
Expert Systems / 6.1: |
Classical Expert Systems / 6.1.1: |
Ontology-Driven Expert Systems / 6.1.2: |
Towards an E-Librarian Service / 6.2: |
Reasoning Capabilities of an E-Librarian Service / 6.2.1: |
Deploying an Ontology / 6.2.2: |
Designing the Ontological Background / 6.2.3: |
Semantic Annotation of the Knowledge Base / 6.3: |
Computer-Assisted Creation of metadata / 6.3.1: |
Automatic Generation of metadata / 6.3.2: |
Design of the Natural Language Processing Module / 7: |
Overview of the Semantic Interpretation / 7.1: |
Logical Form / 7.1.1: |
Processing of a User Question / 7.1.2: |
NLP Pre-Processing / 7.2: |
Domain Language / 7.2.1: |
Lemmatization / 7.2.2: |
Handling Spelling Errors / 7.2.3: |
Ontology Mapping / 7.3: |
Domain Dictionary / 7.3.1: |
Mapping of Words / 7.3.2: |
Resolving Ambiguities / 7.3.3: |
Generation of a DL-Concept Description / 7.4: |
Without Syntactic Analysis / 7.4.1: |
With Syntactic Analysis / 7.4.2: |
How much NLP is Sufficient? / 7.4.3: |
Optimization and Normal Form / 7.4.4: |
General Limitations and Constraints / 7.5: |
Role Quantifiers / 7.5.1: |
Conjunction and Disjunction / 7.5.2: |
Negation / 7.5.3: |
Open-Ended and Closed-Ended Questions / 7.5.4: |
Formulations / 7.5.5: |
Others / 7.5.6: |
Multiple-Language Feature / 7.6: |
Designing the Multimedia Information Retrieval Module / 8: |
Overview of the MIR Module / 8.1: |
Knowledge Base and metadata / 8.1.1: |
Retrieval Principle / 8.1.2: |
The Concept Covering Problem / 8.1.3: |
Identifying Covers / 8.2: |
Computing the Best Covers / 8.3: |
Miss and Rest / 8.3.1: |
Size of a Concept Description / 8.3.2: |
Best Covers / 8.3.3: |
Ranking / 8.4: |
Algorithm for the Retrieval Problem / 8.5: |
User Feedback / 8.6: |
Direct User Feedback / 8.6.1: |
Collaborative Tagging and Social Networks / 8.6.2: |
Diversification of User Feedback / 8.6.3: |
Implementation / 9: |
Knowledge Layer / 9.1: |
Inference Layer / 9.1.2: |
Communication Layer / 9.1.3: |
Presentation Layer / 9.1.4: |
Development Details / 9.2: |
Processing Owl and DL in Java / 9.2.1: |
Client Front-End with Ajax Autocompleter / 9.2.2: |
The Soap Web Service Interface / 9.2.3: |
Applications / Part III: |
Best practices / 10: |
Computer History Expert System (CHESt) / 10.1: |
Description / 10.1.1: |
Experiment / 10.1.2: |
Mathematics Expert System (MatES) / 10.2: |
Benchmark Test / 10.2.1: |
The Lecture Butler's E-Librarian Service / 10.2.3: |
Benchmark Tests / 10.3.1: |
Appendix / Part IV: |
XML Schema Primitive Datatypes / A: |
Reasoning Algorithms / B: |
Structural Subsumption / B.1: |
Example 1 / B.2.1: |
Example 2 / B.2.2: |
Brown Tag Set / C: |
Part-of-Speech Taggers and Parsers / D: |
POS Taggers / D.1: |
Parsers / D.2: |
Probabilistic IR Model / E: |
Probability Theory / E.1: |
References / E.2: |
Index |
Introduction to E-Librarian Services / 1: |
From Ancient to Digital Libraries / 1.1: |
From Searching to Finding / 1.2: |
Searching the Web / 1.2.1: |
Searching Multimedia Knowledge Bases / 1.2.2: |
Exploratory Search / 1.2.3: |