Semantics-Oriented Natural Language Processing. Mathematical Models and Algorithms

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Cover Semantics-Oriented Natural Language Processing: Mathematical Models and Algorithms Semantics-Oriented Natural Language Processing Volume 27 ISBN 0387729240 Preface Content of the Book Acknowledgements Contents Acronyms Part I A Comprehensive Mathematical Framework for the Development of Semantic Technologies 1 Mathematical Models for Designing Natural Language ProcessingSystems as a New Field of Studies for Systems Science 1.1 An Idea of a Bridge Between Systems Science and Engineering of Semantics-Oriented Natural Language Processing Systems 1.2 The Models of Types 1--4 1.2.1 The Models of Type 1 1.2.2 The Models of Type 2 1.2.3 The Models of Type 3 1.2.4 The Models of Type 4 1.3 The Models of Type 5 1.4 The Significance of the Models for the Design of Linguistic Processors 1.5 The Context of Cognitive Linguistics for the Formal Study of Natural Language 1.6 Early Stage of Natural Language Formal Semantics 1.7 The Significance of Highly Expressive Formal Systems of Semantic Representations 2 Introduction to Integral Formal Semantics of Natural Language 2.1 The Basic Principles of Integral Formal Semantics of Natural Language 2.1.1 Basic Principles 2.1.2 The Notion of a Broadly Applicable Conceptual Metagrammar 2.2 The Components of Integral Formal Semanticsof Natural Language 2.3 The Theory of S-Calculuses and S-Languages 2.4 A Model of a Correspondence Between NL-Texts and Their Semantic Representations 2.5 The Theory of T-Calculuses and T-Languages 2.6 The Initial Version of the Theory of K-Calculusesand K-Languages 2.7 The Theory of K-Representations as the Kernel of the Current Version of Integral Formal Semantics 3 A Mathematical Model for Describing a System of Primary Units of Conceptual Level Used by Applied Intelligent Systems 3.1 Global Task Statement 3.2 Local Task Statement 3.3 Basic Denotations and Auxiliary Definitions 3.3.1 General Mathematical Denotations 3.3.2 The Preliminary Definitions from the Theory of Formal Grammars and Languages 3.3.3 The Used Definitions from the Theoryof Algebraic Systems 3.4 The Basic Ideas of the Definition of a Sort System 3.5 The Formal Definition of a Sort System 3.6 Types Generated by a Sort System 3.7 The Concretization Relation on the Set of Types 3.7.1 Basic Ideas 3.7.2 Formal Definitions 3.8 Concept-Object Systems 3.9 Systems of Quantifiers and Logical Connectives:Conceptual Bases 3.10 A Discussion of the Constructed Mathematical Model 3.10.1 Mathematical Peculiarities of the Model 3.10.2 The Comparison of the Model with Related Approaches 4 A Mathematical Model for Describing Structured Meanings of Natural Language Sentences and Discourses 4.1 The Essence of a New Approach to Formalizing Semantic Structure of Natural Language Texts 4.1.1 Toward Expanding the Universe of Formal Study 4.1.2 The Algebraic Essence of the Model Describing Conceptual Operations 4.1.3 Shortly About the Rules for Building Semantic Representations of Natural Language Texts 4.1.4 The Scheme of Determining Three Classes of Formulas Generated by a Conceptual Basis 4.2 The Use of Intensional Quantifiers in Formulas 4.3 The Use of Relational Symbols and the Marking-Up of Formulas 4.3.1 The Rules for Employing Relational Symbols 4.3.2 The Rule for Marking Up the Formulas 4.4 The Use of Logical Connectives NOT, AND, OR 4.5 Building Compound Designations of Notions and Objects 4.5.1 Compound Designations of Notions 4.5.2 Compound Designations of Objects 4.6 Final Rules 4.6.1 The Use of Existential and Universal Quantifiers 4.6.2 The Representations of Finite Sequences 4.6.3 A Summing-Up Information about the Rules P[0]--P[10] 4.7 SK-Languages: Mathematical Investigation of Their Properties 5 A Study of the Expressive Possibilities of SK-Languages 5.1 A Convenient Method of Describing Events 5.2 Formalization of Assumptions About the Structure of Semantic Representations of Sets 5.3 Semantic Representations of Questions with the Role Interrogative Words 5.4 Semantic Representations of Questions About the Quantity of Objects and Events 5.5 Semantic Representations of Questions with an Interrogative Pronoun Attached to a Noun 5.6 Semantic Representations of General Questions 5.7 Describing Semantic Structure of Commands 5.8 Representation of Set-Theoretical Relationships and Operations on Sets 5.9 Semantic Representations of Phrases with Subordinate Clauses of Purpose and Indirect Speech 5.10 Explicit Representation of Causal and Time Relationsin Discourses 5.11 Semantic Representations of Discourses with the Referencesto the Meanings of Phrases and Larger Parts of the Text 5.12 Representing the Pieces of Knowledge About the World 5.13 Object-Oriented Representations of Knowledge Pieces 5.14 The Marked-Up Conceptual Bases 5.15 Related Approaches to Representing Semantic Structureof NL-Texts 6 The Significance of a New Mathematical Model for Web Science, E-science, and E-commerce 6.1 The Problem of Semantic Data Integration 6.1.1 The Purpose of Semantic Data Integration in E-Science and Other E-Fields 6.1.2 Ontologies in Modern Information Society 6.1.3 The Language UNL and the Problem of SharingKnowledge 6.2 Building Semantic Annotations of Web Data 6.3 Conceptual Descriptions of Visual Images 6.4 Representation of Knowledge in Biology and Ecology 6.5 Representation of Knowledge in Medicine 6.6 Representation of Semantic Content in Business 6.7 SK-Languages as a Tool for Building E-Contracts 6.7.1 Formal Languages for E-Contracting 6.7.2 The Possibilities of Forming Contracts and Records of E-Negotiations by Means of SK-Languages 6.8 Simulation of the Expressive Mechanisms of RDF, RDFS,and OWL 6.8.1 Simulation of the Expressive Mechanisms of RDFand RDFs 6.8.2 Simulation of OWL Expressive Mechanisms 6.9 A Metaphor of a Kitchen Combine for the Designers of Semantic Technologies 6.10 The Significance of the Theory of K-Representations for Semantic Web and Web Science 6.10.1 Theory of K-Representations as a Universal Resources and Agents Framework 6.10.2 The Need for the Incentives for Semantic Web 6.10.3 Toward a New Language Platform for Semantic Web 6.10.4 A Possible Strategy of Developing Semantic Webof a New Generation Part II Formal Methods and Algorithms for the Design of Semantics-Oriented Linguistic Processors 7 A Mathematical Model of a Linguistic Database 7.1 The Principles of Designing Semantics-Oriented Linguistic Processors 7.2 Morphological Bases 7.3 Text-Forming Systems 7.4 Lexico-semantic Dictionaries 7.5 Dictionaries of Verbal -- Prepositional Semantic-Syntactic Frames 7.6 The Dictionaries of Prepositional Frames 7.7 Linguistic Bases 7.7.1 Semantic Information Associated with the Role Interrogative Words 7.7.2 The Notion of a Linguistic Basis 8 A New Method of Transforming Texts into SemanticRepresentations 8.1 A Component-Morphological Representation of an NL-text 8.1.1 Morphological Representation 8.1.2 Classifying Representation 8.2 The Projections of the Components of a Linguistic Basison the Input Text 8.3 Matrix Semantic-Syntactic Representations of NL-Texts 8.4 A New Method of Transforming NL-Texts into Semantic Representations 8.4.1 Formulation of the Method 8.4.2 The Principles of Selecting the Form of a Text's Semantic Representation 9 Algorithm of Building a Matrix Semantic-Syntactic Representation of a Natural Language Text 9.1 Task Statement 9.1.1 Purpose of Development and Non-detailed Structureof the Algorithm 9.1.2 Some Peculiarities of the Approach 9.2 Initial Stages of Developing the Algorithm BuildMatr1 9.2.1 External Specification of the Algorithm BuildMatr1 9.2.2 Development of a Plan of the Algorithm BuildMatr1 9.3 Description of the Algorithm Classifying the Input Texts 9.3.1 The Purpose of the Algorithm 9.3.2 Compound Designations of the Subclassesof Lexical Units 9.3.3 External Specification of the Algorithm``Defining-form-of-text'' 9.3.4 Algorithm ``Defining-form-of-text'' 9.4 Principles of Processing the Role Interrogative Words 9.5 An Algorithm of Searching for Semantic Connectionsof the Verbs 9.5.1 Key Ideas of the Algorithm 9.5.2 Description of an Algorithm of Searching for Semantic Connections Between a Verb and a Noun Group 9.5.3 Description of the Algorithm Processing the Constructs 9.5.4 Description of the Algorithm ``Find-set-thematic-roles'' 9.5.5 An Algorithm of Searching for a Semantic Relationship Between a Verb and a Dependent Expression 9.5.6 Final Part of a Description of an Algorithm of Processing Verbs 9.6 Processing of Adjectives, Prepositions, Cardinal Numerals, Names and Nouns 9.6.1 Processing of Adjectives 9.6.2 Processing of Prepositions, Cardinal Numbers,and Names 9.6.3 An Algorithm Searching for Possible Semantic Connections Between Two Nouns with Respectto a Preposition 9.7 Finding the Connections of a Noun with Other Text Units 9.8 Final Step of Developing an Algorithm Building a Matrix Semantic-Syntactic Representation of the Input Text 9.8.1 Description of the Head Module of the Algorithm 9.8.2 External Specifications of Auxiliary Algorithms 9.8.3 Algorithm of Building an MSSR of the Input Text 10 An Algorithm of Semantic Representation Assembly 10.1 Initial Step of Building Semantic Representations of Input Texts 10.1.1 Description of the Algorithm``Preparation-to-constr-SemRepr'' 10.2 Semantic Representations of Short Fragments of the Input Texts 10.2.1 Description of the Algorithm``Calculation-of-the-kind-of-case'' 10.2.2 External Specification of the AlgorithmsBuildSemdes1 -- BuildSemdes7 10.2.3 Description of the AlgorithmsBuildSemdes1 -- BuildSemdes7 10.2.4 Description of the Algorithm ProcessSit 10.2.5 Description of the Algorithm ``Begin-of-constr-SemRepr'' 10.3 Development of the Algorithm ``Representation-of-situations'' 10.3.1 The Key Ideas of the Algorithm 10.3.2 Description of the Algorithm``Representation-of-situations'' 10.4 Final Stages of Developing an Algorithm of Semantic Representation Assembly 10.4.1 External Specification of the Algorithm``Final-operations'' 10.4.2 Algorithm ``Final-operations'' 10.4.3 An Algorithm of Semantic Representation Assembly 10.5 A Multilingual Algorithm of Semantic-Syntactic Analysisof Natural Language Texts 10.5.1 Description of the Algorithm SemSynt1 10.5.2 Some Possible Directions of Using the AlgorithmSemSynt1 11 Natural Language Processing Applications 11.1 The Structure of a Computer Intelligent Agent for Semantic Classification of E-mail Messages 11.1.1 The Problem of Semantic Classificationof E-mail Messages 11.1.2 An Outline of the Computer Intelligent Agent Mailagent1 11.1.3 General Structure of Computer Intelligent AgentMailagent1 11.1.4 The Structure of Semantic-Syntactic Patterns and Lexico-Semantic Dictionary 11.1.5 Implementation Data 11.2 A Transformer of Natural Language Knowledge Descriptionsinto OWL-Expressions A Proofs of Lemmas 1, 2 and Theorem 4.5 from Chapter 4 A.1 Proof of Lemma 1 A.2 Proof of Lemma 2 A.3 Proof of Theorem 4.5 Glossary References Index