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Language Engineering [Kõva köide]

  • Formaat: Hardback, 320 pages, kõrgus x laius: 234x156 mm, kaal: 630 g
  • Ilmumisaeg: 22-Feb-2007
  • Kirjastus: Continuum International Publishing Group Ltd.
  • ISBN-10: 0826482945
  • ISBN-13: 9780826482945
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  • Formaat: Hardback, 320 pages, kõrgus x laius: 234x156 mm, kaal: 630 g
  • Ilmumisaeg: 22-Feb-2007
  • Kirjastus: Continuum International Publishing Group Ltd.
  • ISBN-10: 0826482945
  • ISBN-13: 9780826482945
Teised raamatud teemal:
Independent researcher Georgiev focuses on written language rather than spoken as he examines the discipline and results of natural language processing as it is most closely associated with computer-user interfaces. With extensive examples in English, French and German he describes morphology, syntax and semantics using the C (C++) programming language, with topics including the dictionary of wordforms, procedures to reduce ambiguity, parsing, orthographical rules, German grammatical rules, lexical semantics, representation of knowledge, machine translation, question answering, content recognition (and text attribution to a particular subject field), information retrieval and German and French sequences of speech. This accessible treatment should serve well as a reference suitable for computer scientists, linguists, and practitioners of linguistic programming. Annotation ©2008 Book News, Inc., Portland, OR (booknews.com)
Preface ix
Part one PREPARATORY WORK
1(94)
Dictionary of Wordforms
3(47)
Construction of the Dictionary of Wordforms
5(9)
Protection of the Dictionary of Wordforms
13(1)
C (C++) source code associated with the morphological, grammatical, syntactical and semantical information
14(36)
Recognition of the Prefix
15(3)
Recognition of the compound words separated with a dash
18(1)
Recognition of the abbreviated compound words separated with an inverted comma
19(4)
Recognition of the Umlaut and the accent
23(2)
Recognition of the Parts of Speech by their grammatical ending
25(1)
Case `N', where the code designates a Noun
26(9)
Case `V', where the code designates a Verb
35(10)
Case `A', where the code designates an Adjective
45(4)
Unregistered and unrecognized words
49(1)
Disambiguation procedures
50(10)
Disambiguation instructions programmed in C (C++)
51(3)
General observations and rules
52(2)
Ambiguity Noun or Verb
54(1)
Ambiguity Adjective or Verb
55(1)
Ambiguity Noun or Adjective
55(2)
Ambiguity between Particle and Preposition or Article
57(1)
Ambiguity of an individual word
58(2)
Parsing
60(35)
The Sentence
60(3)
Simple sentence
60(1)
Clause
60(1)
Complex Sentence
61(2)
Parsing of the Sentence
63(6)
Subject
63(1)
Verb
64(1)
Object
64(1)
Complement
65(1)
Complement to the Subject
66(1)
Complement to the Object (Co)
67(1)
Complementing of the Verb
67(2)
Verbal Tenses
69(2)
Parsing instructions programmed in C (C++)
71(20)
Finding the Subject of the Sentence
75(2)
Finding the Object of the Sentence
77(3)
Finding the Complement of the Sentence
80(2)
Recognition of the Verb
82(2)
Recognition of the Verbal Tense
84(7)
Parsing errors
91(4)
Part two SPHERES OF APPLICATION
95(158)
Orthographical Rules
97(10)
Recognition of a misspelt word
98(9)
Grammatical Rules
107(46)
Transfer of grammatical information
107(2)
English grammatical rules
109(20)
Impossible combination of two words
109(1)
Wrong use of -ly when making an Adverb from an Adjective
110(1)
Wrong Use of a Degree
111(1)
Double use of a Degree
112(1)
Impossible Degree Form
112(1)
Wrong use of the Article
113(1)
Wrong use of the Indefinite Article with a Plural Noun
114(1)
Improper matching of the Indefinite Article with the 1st letter (Consonant or Vowel) of the next word
115(1)
Disagreement in Number or Person
116(1)
Wrong use of the Particle to before a Modal Verb
117(1)
Incorrect Verbal Form
118(1)
Incorrect use of the Basic Form of the Verb instead of 3rd Person Singular Present Tense
118(2)
Incorrect use of a Plural Noun with 3rd Person Singular Present Tense of the Verb
120(1)
Erroneous Verbal Form after Auxiliary Verb, plus be
121(1)
Wrong Verbal Form after an Auxiliary Verb from the be paradigm
122(1)
Incorrect use of the Participle after a Modal Verb or an Auxiliary Verb from the shall paradigm
122(1)
Incorrect use of the Basic Form instead of the Participle Form
123(1)
Wrong use of 3rd Person Singular Present Tense after the Verbal Particle to
124(1)
Wrong use of the Verbal Particle to after a Modal Verb or an Auxiliary Verb from the shall paradigm or did, does, done
124(1)
Unrecognized irregular form of a Verb
125(1)
Unrecognized irregular form of a Noun
126(1)
Wrong use of which and who
127(1)
Wrong use of a Preposition
127(2)
German grammatical rules
129(22)
Wrong grammatical ending
129(3)
Wrong agreement between two words in Gender
132(1)
Wrong agreement between two words in Number
133(3)
Wrong agreement between two words in Person
136(2)
Wrong agreement between two words in Case
138(1)
Wrong agreement between Adjective and Noun in Case, Number and Gender
139(2)
Wrong use of haben and its paradigm with a Past Participle
141(1)
Wrong use of sein and its paradigm with a Past Participle
142(1)
Wrong use of zu with forms of the Main Verb
143(2)
Wrong use of a Relative Pronoun or Article after a Transitive or Dative Verb
145(1)
Impossible combination of two words
146(1)
Wrong use of the Reflective Pronoun
146(2)
Wrong use of the Article in Genitive (between two nouns)
148(1)
Wrong reference of a Relative Pronoun
148(1)
Wrong use of a Preposition
149(2)
French grammatical rules
151(1)
Italian grammatical Rules
152(1)
Lexical Semantics
153(24)
Thesauri -- Softhesaurus, Linguaterm and Geoatlas
153(1)
Introduction
153(1)
Purpose and scope
154(1)
Presentation
154(20)
Syntagmatical Synonyms
155(5)
Word Class
160(5)
Substitute word
165(1)
Part of
166(1)
Located in
167(1)
Narrower meaning -- broader meaning
167(1)
One -- many
167(2)
Smaller -- bigger
169(1)
Synonyms and thesaurus
169(1)
Subject field
170(1)
Modal sem
171(1)
Links
172(1)
Other types of relationships in the ALSD
172(2)
Discussion
174(3)
Representation of knowledge
177(2)
Machine Translation
179(29)
Construction of the bilingual dictionary
179(4)
Source code used to define the information about the word
183(4)
Choosing of the right meaning depending on context
187(3)
Choosing of the correct grammatical ending for the translated word
190(10)
Choosing of the right word sequence for the target language
200(3)
Blocking a word in the translation
203(1)
Inserting a word in the translation
204(2)
Known difficulties and problems
206(2)
Question Answering
208(35)
Dividing the knowledge about the word and the world into fields and groups
208(2)
Adding semantical, pragmatical, etc. information to each word in the DW and programming this information
210(6)
Making a list of all possible questions. Examples
216(2)
Ready-made answer to a question, presented only in the DW. Examples
218(1)
Programmed answer to a particular question. Examples
219(24)
Content Recognition and Text Attribution to a particular subject field
243(5)
How to use the meaning of the word-groups for text attribution
243(1)
Making a list of all possible subject fields. Example
243(1)
Counting the occurences of a particular meaning in a text for decision making
244(4)
Information Retrieval
248(3)
German and French Sequences of Parts of Speech
251(2)
List of abbreviations
253(4)
References
257(4)
Appendices
261(46)
German dictionary of segments
261(6)
French dictionary of segments
267(5)
Sample of source code compilable on a Borland compiler versions 2-4.52
272(35)
Index 307


Dr Hristo Georgiev is an independent researcher in Natural Language Processing.