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Automatic Indexing and Abstracting of Document Texts

:	Marie Francine Moens
:	Automatic Indexing and Abstracting of Document Texts
:	Kluwer Academic Publishers
:	9780306470172
:	1
:	CHF 113.60
:

:	Naturwissenschaft
:	English

:	284
:	DRM
:	PC/MAC/eReader/Tablet
:	PDF

Automatic Indexing and Abstracting of Document Texts summarizes the latest techniques of automatic indexing and abstracting, and the results of their application. It also places the techniques in the context of the study of text, manual indexing and abstracting, and the use of the indexing descriptions and abstracts in systems that select documents or information from large collections. Important sections of the book consider the development of new techniques for indexing and abstracting. The techniques involve the following: using text grammars, learning of the themes of the texts including the identification of representative sentences or paragraphs by means of adequate cluster algorithms, and learning of classification patterns of texts. In addition, the book is an attempt to illuminate new avenues for future research. Automatic Indexing and Abstracting of Document Texts is an excellent reference for researchers and professionals working in the field of content management and information retrieval.

	CONTENTS	7
	PREFACE	11
	ACKNOWLEDGEMENTS	15
	PART I THE INDEXING AND ABSTRACTING ENVIRONMENT	18
	Chapter 1 THE NEED FOR INDEXING AND ABSTRACTING TEXTS	19
	1. INTRODUCTION	19
	2. ELECTRONIC DOCUMENTS	20
	3. COMMUNICATION THROUGH NATURAL LANGUAGE TEXT	21
	4. UNDERSTANDING OF NATURAL LANGUAGE TEXT: THE COGNITIVE PROCESS	23
	5. UNDERSTANDING OF NATURAL LANGUAGE TEXT: THE AUTOMATED PROCESS	24
	6. IMPORTANT CONCEPTS IN INFORMATION RETRIEVAL AND SELECTION	26
	7. GENERAL SOLUTIONS TO THE INFORMATION RETRIEVAL PROBLEM	33
	8. THE NEED FOR BETTER AUTOMATIC INDEXING AND ABSTRACTING TECHNIQUES	38
	Chapter 2 THE ATTRIBUTES OF TEXT	43
	1. INTRODUCTION	43
	2. THE STUDY OF TEXT	43
	3. AN OVERVIEW OF SOME COMMON TEXT TYPES	45
	4. TEXT DESCRIBED AT A MICRO LEVEL	46
	5. TEXT DESCRIBED AT A MACRO LEVEL	54
	6. CONCLUSIONS	63
	Chapter 3 TEXT REPRESENTATIONS AND THEIR USE	65
	1. INTRODUCTION	65
	2. DEFINITIONS	65
	3. REPRESENTATIONS THAT CHARACTERIZE THE CONTENT OF TEXT 3.1 Set of Natural Language Index Terms	66
	4. INTELLECTUAL INDEXING AND ABSTRACTING 4.1 Gene ral	71
	5. USE OF THE TEXT REPRESENTATIONS	76
	6. A NOTE ABOUT THE STORAGE OF TEXT REPRESENTATIONS	85
	7. CHARACTERISTICS OF GOOD TEXT REPRESENTATIONS	86
	8. CONCLUSIONS	89
	PART II METHODS OF AUTOMATIC INDEXING AND ABSTRACTING	91
	Chapter 4 AUTOMATIC INDEXING: THE SELECTION OF NATURAL LANGUAGE INDEX TERMS	93
	1. INTRODUCTION	93
	2. A NOTE ABOUT EVALUATION	94
	3. LEXICAL ANALYSIS	94
	4. USE OF A STOPLIST	96
	5. STEMMING	97
	6. THE SELECTION OF PHRASES	100
	7. INDEX TERM WEIGHTING	105
	8. ALTERNATIVE PROCEDURES FOR SELECTING INDEX TERMS	114
	9. SELECTION OF NATURAL LANGUAGE INDEX TERMS: ACCOMPLISHMENTS AND PROBLEMS	117
	10. CONCLUSIONS	118
	Chapter 5 AUTOMATIC INDEXING: THE ASSIGNMENT OF CONTROLLED LANGUAGE INDEX TERMS	119
	1. INTRODUCTION	119
	2. A NOTE ABOUT EVALUATION	120
	3. THESAURUS TERMS	122
	4. SUBJECT AND CLASSIFICATION CODES	127
	5. LEARNING APPROACHES TO TEXT CATEGORIZATION	131
	6. ASSIGNMENT OF CONTROLLED LANGUAGE INDEX TERMS: ACCOMPLISHMENTS AND PROBLEMS	147
	7. CONCLUSIONS	148
	Chapter 6 AUTOMATIC ABSTRACTING: THE CREATION OF TEXT SUMMARIES	149
	1. INTRODUCTION	149
	2. A NOTE ABOUT EVALUATION	150
	3. THE TEXT ANALYSIS STEP	152
	4. THE TRANSFORMATION STEP 4.1 Selection and Generalization of the Content	164
	5. GENERATION OF THE ABSTRACT	166
	6. TEXT ABSTRACTING: ACCOMPLISHMENTS AND PROBLEMS	168
	7. CONCLUSIONS	170
	PART III APPLICATIONS	172
	Chapter 7 TEXT STRUCTURING AND CATEGORIZATION WHEN SUMMARIZING LEGAL CASES	173
	1. INTRODUCTION	173
	2. TEXT CORPUS AND OUTPUT OF THE SYSTEM	174
	3. METHODS: THE USE OF A TEXT GRAMMAR	177
	4. RESULTS AND DISCUSSION	181
	5. CONTRIBUTIONS OF THE RESEARCH	184
	6. CONCLUSIONS	188
	Chapter 8 CLUSTERING OF PARAGRAPHS WHEN SUMMARIZING LEGAL CASES	189
	1. INTRODUCTION	189
	2. TEXT CORPUS AND OUTPUT OF THE SYSTEM	190
	3. METHODS: THE CLUSTERING TECHNIQUES	191
	4. RESULTS AND DISCUSSION	197
	5. CONTRIBUTIONS OF THE RESEARCH	204
	6. CONCLUSIONS	206
	Chapter 9 THE CREATION OF HIGHLIGHT ABSTRACTS OF MAGAZINE ARTICLES	207
	1. INTRODUCTION	207
	2. TEXT CORPUS AND OUTPUT OF THE SYSTEM	208
	3. METHODS: THE USE OF A TEXT GRAMMAR	210
	4. RESULTS AND DISCUSSION	217
	5. CONTRIBUTIONS OF THE RESEARCH	220
	6. CONCLUSIONS	221
	Chapter 10 THE ASSIGNMENT OF SUBJECT DESCRIPTORS TO MAGAZINE ARTICLES	223
	1. INTRODUCTION	223
	2. TEXT CORPUS AND OUTPUT OF THE SYSTEM	224
	3. METHODS: SUPERVISED LEARNING OF CLASSIFICATION PATTERNS	226
	4. RESULTS AND DISCUSSION	233
	5. CONTRIBUTIONS OF THE RESEARCH	240
	6. CONCLUSIONS	241
	SUMMARY AND FUTURE PROSPECTS	243
	1. SUMMARY	243
	2. FUTURE PROSPECTS	251
	REFERENCES	253
	SUBJECT INDEX	277