Semantics-oriented natural language processing: mathematical models and algorithms
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New York [u.a.]
Springer
2010
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| Schriftenreihe: | IFSR international series on systems science and engineering
26 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XXIII, 328 S. graph. Darst. 235 mm x 155 mm |
| ISBN: | 9780387729244 0387729240 |
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| 245 | 1 | 0 | |a Semantics-oriented natural language processing |b mathematical models and algorithms |c Vladimir A. Fomichov |
| 264 | 1 | |a New York [u.a.] |b Springer |c 2010 | |
| 300 | |a XXIII, 328 S. |b graph. Darst. |c 235 mm x 155 mm | ||
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| 490 | 1 | |a IFSR international series on systems science and engineering |v 26 | |
| 650 | 4 | |a Natural language processing (Computer science) | |
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Datensatz im Suchindex
| _version_ | 1804138608652713984 |
|---|---|
| adam_text | VLADIMIR A. FOMICHOV SEMANTICS-ORIENTED NATURAL LANGUAGE PROCESSING
MATHEMATICAL MODELS AND ALGORITHMS 4Y SPRINGER CONTENTS PART I A
COMPREHENSIVE MATHEMATICAL FRAMEWORK FOR THE DEVELOPMENT OF SEMANTIC
TECHNOLOGIES 1 MATHEMATICAL MODELS FOR DESIGNING NATURAL LANGUAGE
PROCESSING SYSTEMS AS A NEW FIELD OF STUDIES FOR SYSTEMS SCIENCE 3 1.1
AN IDEA OF A BRIDGE BETWEEN SYSTEMS SCIENCE AND ENGINEERING OF
SEMANTICS-ORIENTED NATURAL LANGUAGE PROCESSING SYSTEMS 3 1.2 THE MODELS
OF TYPES 1^ 5 1.2.1 THE MODELS OF TYPE 1 5 1.2.2 THE MODELS OF TYPE 2 7
K2.3 THE MODELS OF TYPE 3 7 1.2.4 THE MODELS OF TYPE 4 10 1.3 THE MODELS
OF TYPE 5 11 1.4 THE SIGNIFICANCE OF THE MODELS FOR THE DESIGN OF
LINGUISTIC PROCESSORS 16 1.5 THE CONTEXT OF COGNITIVE LINGUISTICS FOR
THE FORMAL STUDY OF NATURAL LANGUAGE 17 1.6 EARLY STAGE OF NATURAL
LANGUAGE FORMAL SEMANTICS 18 1.7 THE SIGNIFICANCE OF HIGHLY EXPRESSIVE
FORMAL SYSTEMS OF SEMANTIC REPRESENTATIONS 22 2 INTRODUCTION TO INTEGRAL
FORMAL SEMANTICS OF NATURAL LANGUAGE .... 27 2. 1 THE BASIC PRINCIPLES
OF INTEGRAL FORMAL SEMANTICS OF NATURAL LANGUAGE 27 2.1.1 BASIC
PRINCIPLES 27 2.1.2 THE NOTION OF A BROADLY APPLICABLE CONCEPTUAL
METAGRAMMAR 29 2.2 THE COMPONENTS OF INTEGRAL FORMAL SEMANTICS OF
NATURAL LANGUAGE 30 2.3 THE THEORY OF S-CALCULUSES AND S-LANGUAGES 32
2.4 A MODEL OF A CORRESPONDENCE BETWEEN NL-TEXTS AND THEIR SEMANTIC
REPRESENTATIONS 37 CONTENTS 2.5 THE THEORY OF T-CALCULUSES AND
T-LANGUAGES 38 2.6 THE INITIAL VERSION OF THE THEORY OF K-CALCULUSES AND
K-LANGUAGES 39 2.7 THE THEORY OF K-REPRESENTATIONS AS THE KERNEL OF THE
CURRENT VERSION OF INTEGRAL FORMAL SEMANTICS 41 A MATHEMATICAL MODEL FOR
DESCRIBING A SYSTEM OF PRIMARY UNITS OF CONCEPTUAL LEVEL USED BY APPLIED
INTELLIGENT SYSTEMS 43 3.1 GLOBAL TASK STATEMENT 43 3.2 LOCAL TASK
STATEMENT 47 3.3 BASIC DENOTATIONS AND AUXILIARY DEFINITIONS 48 3.3.1
* GENERAL MATHEMATICAL DENOTATIONS 48 3.3.2 THE PRELIMINARY DEFINITIONS
FROM THE THEORY OF FORMAL GRAMMARS AND LANGUAGES 48 3.3.3 THE USED
DEFINITIONS FROM THE THEORY OF ALGEBRAIC SYSTEMS 49 3.4 THE BASIC IDEAS
OF THE DEFINITION OF A SORT SYSTEM 50 3.5 THE FORMAL DEFINITION OF A
SORT SYSTEM 52 3.6 TYPES GENERATED BY A SORT SYSTEM 55 3.7 THE
CONCRETIZATION RELATION ON THE SET OF TYPES 58 3.7.1 BASIC IDEAS 58
3.7.2 FORMAL DEFINITIONS 60 3.8 CONCEPT-OBJECT SYSTEMS 64 3.9 SYSTEMS OF
QUANTIFIERS AND LOGICAL CONNECTIVES: CONCEPTUAL BASES 67 3.10 A
DISCUSSION OF THE CONSTRUCTED MATHEMATICAL MODEL 71 3.10.1 MATHEMATICAL
PECULIARITIES OF THE MODEL 71 3.10.2 THE COMPARISON OF THE MODEL WITH
RELATED APPROACHES ... 72 A MATHEMATICAL MODEL FOR DESCRIBING STRUCTURED
MEANINGS OF NATURAL LANGUAGE SENTENCES AND DISCOURSES 77 4. 1 THE
ESSENCE OF A NEW APPROACH TO FORMALIZING SEMANTIC STRUCTURE OF NATURAL
LANGUAGE TEXTS 77 4.1.1 TOWARD EXPANDING THE UNIVERSE OF FORMAL STUDY 77
4.1.2 THE ALGEBRAIC ESSENCE OF THE MODEL DESCRIBING CONCEPTUAL
OPERATIONS 80 4.1.3 SHORTLY ABOUT THE RULES FOR BUILDING SEMANTIC
REPRESENTATIONS OF NATURAL LANGUAGE TEXTS 81 4.1.4 THE SCHEME OF
DETERMINING THREE CLASSES OF FORMULAS GENERATED BY A CONCEPTUAL BASIS 84
4.2 THE USE OF INTENSIONAL QUANTIFIERS IN FORMULAS 86 4.3 THE USE OF
RELATIONAL SYMBOLS AND THE MARKING-UP OF FORMULAS 92 4.3.1 THE RULES FOR
EMPLOYING RELATIONAL SYMBOLS 92 4.3.2 THE RULE FOR MARKING UP THE
FORMULAS 96 CONTENTS XVII 4.4 THE USE OF LOGICAL CONNECTIVES NOT, AND,
OR 97 4.5 BUILDING COMPOUND DESIGNATIONS OF NOTIONS AND OBJECTS 99 4.5.1
COMPOUND DESIGNATIONS OF NOTIONS 99 4.5.2 COMPOUND DESIGNATIONS OF
OBJECTS 101 4.6 FINAL RULES 102 4.6.1 THE USE OF EXISTENTIAL AND
UNIVERSAL QUANTIFIERS 102 4.6.2 THE REPRESENTATIONS OF FINITE SEQUENCES
104 4.6.3 A SUMMING-UP INFORMATION ABOUT THE RULES P[0]-P[10] ... 105
4.7 SK-LANGUAGES: MATHEMATICAL INVESTIGATION OF THEIR PROPERTIES 107 5 A
STUDY OF THE EXPRESSIVE POSSIBILITIES OF SK-LANGUAGES 113 5.1 A
CONVENIENT METHOD OF DESCRIBING EVENTS 113 5.2 FORMALIZATION OF
ASSUMPTIONS ABOUT THE STRUCTURE OF SEMANTIC REPRESENTATIONS OF SETS 115
5.3 SEMANTIC REPRESENTATIONS OF QUESTIONS WITH THE ROLE INTERROGATIVE
WORDS 118 5.4 SEMANTIC REPRESENTATIONS OF QUESTIONS ABOUT THE QUANTITY
OF OBJECTS AND EVENTS 120 5.5 SEMANTIC REPRESENTATIONS OF QUESTIONS WITH
AN INTERROGATIVE PRONOUN ATTACHED TO A NOUN 121 5.6 SEMANTIC
REPRESENTATIONS OF GENERAL QUESTIONS 122 5.7 DESCRIBING SEMANTIC
STRUCTURE OF COMMANDS 123 5.8 REPRESENTATION OF SET-THEORETICAL
RELATIONSHIPS AND OPERATIONS ON SETS 123 5.9 SEMANTIC REPRESENTATIONS OF
PHRASES WITH SUBORDINATE CLAUSES OF PURPOSE AND INDIRECT SPEECH 124 5.10
EXPLICIT REPRESENTATION OF CAUSAL AND TIME RELATIONS IN DISCOURSES 125
5.11 SEMANTIC REPRESENTATIONS OF DISCOURSES WITH THE REFERENCES TO THE
MEANINGS OF PHRASES AND LARGER PARTS OF THE TEXT 127 5.12 REPRESENTING
THE PIECES OF KNOWLEDGE ABOUT THE WORLD 127 5.13 OBJECT-ORIENTED
REPRESENTATIONS OF KNOWLEDGE PIECES 128 5.14 THE MARKED-UP CONCEPTUAL
BASES 129 5.15 RELATED APPROACHES TO REPRESENTING SEMANTIC STRUCTURE OF
NL-TEXTS 131 6 THE SIGNIFICANCE OF A NEW MATHEMATICAL MODEL FOR WEB
SCIENCE, E-SCIENCE, AND E-COMMERCE 137 6.1 THE PROBLEM OF SEMANTIC DATA
INTEGRATION 137 6.1.1 THE PURPOSE OF SEMANTIC DATA INTEGRATION IN
E-SCIENCE AND OTHER E-FIELDS 137 6.1.2 ONTOLOGIES IN MODERN INFORMATION
SOCIETY 138 6.1.3 THE LANGUAGE UNL AND THE PROBLEM OF SHARING KNOWLEDGE
139 XVIII CONTENTS 6.2 BUILDING SEMANTIC ANNOTATIONS OF WEB DATA 140 6.3
CONCEPTUAL DESCRIPTIONS OF VISUAL IMAGES 143 6.4 REPRESENTATION OF
KNOWLEDGE IN BIOLOGY AND ECOLOGY 145 6.5 REPRESENTATION OF KNOWLEDGE IN
MEDICINE 147 6.6 REPRESENTATION OF SEMANTIC CONTENT IN BUSINESS 148 6.7
SK-LANGUAGES AS A TOOL FOR BUILDING E-CONTRACTS 149 6.7.1 FORMAL
LANGUAGES FOR E-CONTRACTING 149 6.7.2 THE POSSIBILITIES OF FORMING
CONTRACTS AND RECORDS OF E-NEGOTIATIONS BY MEANS OF SK-LANGUAGES 150 6.8
SIMULATION OF THE EXPRESSIVE MECHANISMS OF RDF, RDFS, . AND OWL 152
6.8.1 SIMULATION OF THE EXPRESSIVE MECHANISMS OF RDF AND RDFS 152
6.8.2 SIMULATION OF OWL EXPRESSIVE MECHANISMS 155 6.9 A METAPHOR OF A
KITCHEN COMBINE FOR THE DESIGNERS OF SEMANTIC TECHNOLOGIES 156 6.10 THE
SIGNIFICANCE OF THE THEORY OF K-REPRESENTATIONS FOR SEMANTIC WEB AND WEB
SCIENCE 158 6.10.1 THEORY OF K-REPRESENTATIONS AS A UNIVERSAL RESOURCES
AND AGENTS FRAMEWORK 158 6.10.2 THE NEED FOR THE INCENTIVES FOR SEMANTIC
WEB 159 6.10.3 TOWARD A NEW LANGUAGE PLATFORM FOR SEMANTIC WEB 160
6.10.4 A POSSIBLE STRATEGY OF DEVELOPING SEMANTIC WEB OF A NEW
GENERATION 160 PART II FORMAL METHODS AND ALGORITHMS FOR THE DESIGN OF
SEMANTICS-ORIENTED LINGUISTIC PROCESSORS 7 A MATHEMATICAL MODEL OF A
LINGUISTIC DATABASE 1 65 7.1 THE PRINCIPLES OF DESIGNING
SEMANTICS-ORIENTED LINGUISTIC PROCESSORS 165 7.2 MORPHOLOGICAL BASES 167
7.3 TEXT-FORMING SYSTEMS 171 7.4 LEXICO-SEMANTIC DICTIONARIES 173 7.5
DICTIONARIES OF VERBAL - PREPOSITIONAL SEMANTIC-SYNTACTIC FRAMES .. 175
7.6 THE DICTIONARIES OF PREPOSITIONAL FRAMES 179 7.7 LINGUISTIC BASES
181 7.7.1 SEMANTIC INFORMATION ASSOCIATED WITH THE ROLE INTERROGATIVE
WORDS 181 7.7.2 THE NOTION OF A LINGUISTIC BASIS 1 82 8 A NEW METHOD OF
TRANSFORMING TEXTS INTO SEMANTIC REPRESENTATIONS 185 8.1 A
COMPONENT-MORPHOLOGICAL REPRESENTATION OF AN NL-TEXT 185 8.1.1
MORPHOLOGICAL REPRESENTATION 185 8.1.2 CLASSIFYING REPRESENTATION 187
CONTENTS 8.2 THE PROJECTIONS OF THE COMPONENTS OF A LINGUISTIC BASIS ON
THE INPUT TEXT ... . 189 8.3 MATRIX SEMANTIC-SYNTACTIC REPRESENTATIONS
OF NL-TEXTS 192 8.4 A NEW METHOD OF TRANSFORMING NL-TEXTS INTO SEMANTIC
REPRESENTATIONS 194 8.4.1 FORMULATION OF THE METHOD 194 8.4.2 THE
PRINCIPLES OF SELECTING THE FORM OF A TEXT S SEMANTIC REPRESENTATION 196
ALGORITHM OF BUILDING A MATRIX SEMANTIC-SYNTACTIC REPRESENTATION OF A
NATURAL LANGUAGE TEXT 201 9.1 TASK STATEMENT 201 9.1.1 PURPOSE OF
DEVELOPMENT AND NON-DETAILED STRUCTURE OF THE ALGORITHM 201 9.1.2 SOME
PECULIARITIES OF THE APPROACH 202 9.2 INITIAL STAGES OF DEVELOPING THE
ALGORITHM BUILDMATRL 204 9.2.1 EXTERNAL SPECIFICATION OF THE ALGORITHM
BUILDMATRL 204 9.2.2 DEVELOPMENT OF A PLAN OF THE ALGORITHM BUILDMATRL
204 9.3 DESCRIPTION OF THE ALGORITHM CLASSIFYING THE INPUT TEXTS 205
9.3.1 THE PURPOSE OF THE ALGORITHM 205 9.3.2 COMPOUND DESIGNATIONS OF
THE SUBCLASSES OF LEXICAL UNITS 207 9.3.3 EXTERNAL SPECIFICATION OF THE
ALGORITHM DEFINING-FORM-OF-TEXT 208 9.3.4 ALGORITHM
DEFINING-FORM-OF-TEXT 209 9.4 PRINCIPLES OF PROCESSING THE ROLE
INTERROGATIVE WORDS 212 9.5 AN ALGORITHM OF SEARCHING FOR SEMANTIC
CONNECTIONS OF THE VERBS 215 9.5.1 KEY IDEAS OF THE ALGORITHM 216 9.5.2
DESCRIPTION OF AN ALGORITHM OF SEARCHING FOR SEMANTIC CONNECTIONS
BETWEEN A VERB AND A NOUN GROUP 217 9.5.3 DESCRIPTION OF THE ALGORITHM
PROCESSING THE CONSTRUCTS .... 221 9.5.4 DESCRIPTION OF THE ALGORITHM
FIND-SET-THEMATIC-ROLES .... 223 9.5.5 AN ALGORITHM OF SEARCHING FOR A
SEMANTIC RELATIONSHIP BETWEEN A VERB AND A DEPENDENT EXPRESSION 224
9.5.6 FINAL PART OF A DESCRIPTION OF AN ALGORITHM OF PROCESSING VERBS
227 9.6 PROCESSING OF ADJECTIVES, PREPOSITIONS, CARDINAL NUMERALS, NAMES
AND NOUNS 229 9.6.1 PROCESSING OF ADJECTIVES 229 9.6.2 PROCESSING OF
PREPOSITIONS, CARDINAL NUMBERS, AND NAMES 230 9.6.3 AN ALGORITHM
SEARCHING FOR POSSIBLE SEMANTIC CONNECTIONS BETWEEN TWO NOUNS WITH
RESPECT TO A PREPOSITION 231 XX CONTENTS 9.7 FINDING THE CONNECTIONS OF
A NOUN WITH OTHER TEXT UNITS 235 9.8 FINAL STEP OF DEVELOPING AN
ALGORITHM BUILDING A MATRIX SEMANTIC-SYNTACTIC REPRESENTATION OF THE
INPUT TEXT 244 9.8.1 DESCRIPTION OF THE HEAD MODULE OF THE ALGORITHM 244
9.8.2 EXTERNAL SPECIFICATIONS OF AUXILIARY ALGORITHMS 245 9.8.3
ALGORITHM OF BUILDING AN MSSR OF THE INPUT TEXT 246 10 AN ALGORITHM OF
SEMANTIC REPRESENTATION ASSEMBLY 249 10.1 INITIAL STEP OF BUILDING
SEMANTIC REPRESENTATIONS OF INPUT TEXTS ... 249 10.1.1 DESCRIPTION OF
THE ALGORITHM PREPARATION-TO-CONSTR-SEMREPR 250 10.2 SEMANTIC
REPRESENTATIONS OF SHORT FRAGMENTS OF THE INPUT TEXTS ... 254 10.2.1
DESCRIPTION OF THE ALGORITHM CALCULATION-OF-THE-KIND-OF-CASE 254
10.2.2 EXTERNAL SPECIFICATION OF THE ALGORITHMS BUILDSEMDESL
-BUILDSEMDES7 256 10.2.3 DESCRIPTION OF THE ALGORITHMS BUILDSEMDESL
-BUILDSEMDES7 257 10.2.4 DESCRIPTION OF THE ALGORITHM PROCESSSIT 262
10.2.5 DESCRIPTION OF THE ALGORITHM BEGIN-OF-CONSTR-SEMREPR .. 264
10.3 DEVELOPMENT OF THE ALGORITHM REPRESENTATION-OF-SITUATIONS 265
10.3.1 THE KEY IDEAS OF THE ALGORITHM 265 10.3.2 DESCRIPTION OF THE
ALGORITHM REPRESENTATION-OF-SITUATIONS 268 10.4 FINAL STAGES OF
DEVELOPING AN ALGORITHM OF SEMANTIC REPRESENTATION ASSEMBLY 273 10.4.1
EXTERNAL SPECIFICATION OF THE ALGORITHM FINAL-OPERATIONS 274 10.4.2
ALGORITHM FINAL-OPERATIONS 275 10.4.3 AN ALGORITHM OF SEMANTIC
REPRESENTATION ASSEMBLY 280 10.5 A MULTILINGUAL ALGORITHM OF
SEMANTIC-SYNTACTIC ANALYSIS OF NATURAL LANGUAGE TEXTS 281 10.5.1
DESCRIPTION OF THE ALGORITHM SEMSYNTL 281 10.5.2 SOME POSSIBLE
DIRECTIONS OF USING THE ALGORITHM SEMSYNTL 282 11 NATURAL LANGUAGE
PROCESSING APPLICATIONS 285 11.1 THE STRUCTURE OF A COMPUTER INTELLIGENT
AGENT FOR SEMANTIC CLASSIFICATION OF E-MAIL MESSAGES 285 11.1.1 THE
PROBLEM OF SEMANTIC CLASSIFICATION OF E-MAIL MESSAGES 285 11.1.2 AN
OUTLINE OF THE COMPUTER INTELLIGENT AGENT MAILAGENTL ..286 11.1.3
GENERAL STRUCTURE OF COMPUTER INTELLIGENT AGENT MAILAGENTL 288 11.1.4
THE STRUCTURE OF SEMANTIC-SYNTACTIC PATTERNS AND LEXICO-SEMANTIC
DICTIONARY 288 11.1.5 IMPLEMENTATION DATA 293 CONTENTS XXI 11.2 A
TRANSFORMER OF NATURAL LANGUAGE KNOWLEDGE DESCRIPTIONS INTO
OWL-EXPRESSIONS 293 A PROOFS OF LEMMAS 1, 2 AND THEOREM 4.5 FROM CHAPTER
4 299 A. 1 PROOF OF LEMMA 1 299 A.2 PROOF OF LEMMA 2 302 A.3 PROOF OF
THEOREM 4.5 304 GLOSSARY 313 REFERENCES 315 INDEX * 327
|
| any_adam_object | 1 |
| author | Fomichov, Vladimir A. |
| author_facet | Fomichov, Vladimir A. |
| author_role | aut |
| author_sort | Fomichov, Vladimir A. |
| author_variant | v a f va vaf |
| building | Verbundindex |
| bvnumber | BV035306239 |
| callnumber-first | Q - Science |
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| callnumber-raw | QA76.9.N38 |
| callnumber-search | QA76.9.N38 |
| callnumber-sort | QA 276.9 N38 |
| callnumber-subject | QA - Mathematics |
| classification_rvk | ST 306 |
| ctrlnum | (OCoLC)435731453 (DE-599)DNB985875135 |
| dewey-full | 006.35 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.35 |
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| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik Mathematik |
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| id | DE-604.BV035306239 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T21:30:54Z |
| institution | BVB |
| isbn | 9780387729244 0387729240 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-017111033 |
| oclc_num | 435731453 |
| open_access_boolean | |
| owner | DE-19 DE-BY-UBM DE-473 DE-BY-UBG DE-11 |
| owner_facet | DE-19 DE-BY-UBM DE-473 DE-BY-UBG DE-11 |
| physical | XXIII, 328 S. graph. Darst. 235 mm x 155 mm |
| publishDate | 2010 |
| publishDateSearch | 2010 |
| publishDateSort | 2010 |
| publisher | Springer |
| record_format | marc |
| series | IFSR international series on systems science and engineering |
| series2 | IFSR international series on systems science and engineering |
| spelling | Fomichov, Vladimir A. Verfasser aut Semantics-oriented natural language processing mathematical models and algorithms Vladimir A. Fomichov New York [u.a.] Springer 2010 XXIII, 328 S. graph. Darst. 235 mm x 155 mm txt rdacontent n rdamedia nc rdacarrier IFSR international series on systems science and engineering 26 Natural language processing (Computer science) Semantics Natürliche Sprache (DE-588)4041354-8 gnd rswk-swf Semantik (DE-588)4054490-4 gnd rswk-swf Sprachverarbeitung (DE-588)4116579-2 gnd rswk-swf Natürliche Sprache (DE-588)4041354-8 s Semantik (DE-588)4054490-4 s Sprachverarbeitung (DE-588)4116579-2 s DE-604 IFSR international series on systems science and engineering 26 (DE-604)BV000016922 26 HEBIS Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017111033&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Fomichov, Vladimir A. Semantics-oriented natural language processing mathematical models and algorithms IFSR international series on systems science and engineering Natural language processing (Computer science) Semantics Natürliche Sprache (DE-588)4041354-8 gnd Semantik (DE-588)4054490-4 gnd Sprachverarbeitung (DE-588)4116579-2 gnd |
| subject_GND | (DE-588)4041354-8 (DE-588)4054490-4 (DE-588)4116579-2 |
| title | Semantics-oriented natural language processing mathematical models and algorithms |
| title_auth | Semantics-oriented natural language processing mathematical models and algorithms |
| title_exact_search | Semantics-oriented natural language processing mathematical models and algorithms |
| title_full | Semantics-oriented natural language processing mathematical models and algorithms Vladimir A. Fomichov |
| title_fullStr | Semantics-oriented natural language processing mathematical models and algorithms Vladimir A. Fomichov |
| title_full_unstemmed | Semantics-oriented natural language processing mathematical models and algorithms Vladimir A. Fomichov |
| title_short | Semantics-oriented natural language processing |
| title_sort | semantics oriented natural language processing mathematical models and algorithms |
| title_sub | mathematical models and algorithms |
| topic | Natural language processing (Computer science) Semantics Natürliche Sprache (DE-588)4041354-8 gnd Semantik (DE-588)4054490-4 gnd Sprachverarbeitung (DE-588)4116579-2 gnd |
| topic_facet | Natural language processing (Computer science) Semantics Natürliche Sprache Semantik Sprachverarbeitung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017111033&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV000016922 |
| work_keys_str_mv | AT fomichovvladimira semanticsorientednaturallanguageprocessingmathematicalmodelsandalgorithms |