Introduction to information retrieval:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cambridge [u.a.]
Cambridge Univ. Press
2008
|
| Ausgabe: | 1. publ. |
| Schlagworte: | |
| Online-Zugang: | Volltext Publisher description Inhaltsverzeichnis |
| Beschreibung: | Hier auch später erschienene, unveränderte Nachdrucke |
| Beschreibung: | XXI, 482 S. graph. Darst. |
| ISBN: | 9780521865715 0521865719 |
Internformat
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| 100 | 1 | |a Manning, Christopher D. |d 1965- |e Verfasser |0 (DE-588)172764629 |4 aut | |
| 245 | 1 | 0 | |a Introduction to information retrieval |c Christopher D. Manning ; Prabhakar Raghavan ; Hinrich Schütze |
| 250 | |a 1. publ. | ||
| 264 | 1 | |a Cambridge [u.a.] |b Cambridge Univ. Press |c 2008 | |
| 300 | |a XXI, 482 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 500 | |a Hier auch später erschienene, unveränderte Nachdrucke | ||
| 650 | 4 | |a Text processing (Computer science) | |
| 650 | 4 | |a Information retrieval | |
| 650 | 4 | |a Document clustering | |
| 650 | 4 | |a Semantic Web | |
| 650 | 0 | 7 | |a Abfrageverarbeitung |0 (DE-588)4378490-2 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Semantic Web |0 (DE-588)4688372-1 |2 gnd |9 rswk-swf |
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| 650 | 0 | 7 | |a Information Retrieval |0 (DE-588)4072803-1 |2 gnd |9 rswk-swf |
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| 700 | 1 | |a Schütze, Hinrich |e Sonstige |0 (DE-588)112281672 |4 oth | |
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Datensatz im Suchindex
| _version_ | 1804138075589181440 |
|---|---|
| adam_text | Contents
Table of
Notation
page
xi
Preface
xv
1
Boolean retrieval
1
1.1
An example information retrieval problem
3
1.2
A first take at building an inverted index
6
1.3
Processing Boolean queries
9
1.4
The extended Boolean model versus ranked retrieval
13
1.5
References and further reading
16
2
The term vocabulary ana postings lists
18
2.1
Document delineation and character sequence decoding
18
2.2
Determining the vocabulary of terms
21
2.3
Faster postings list intersection via skip pointers
33
2.4
Positional postings and phrase queries
36
2.5
References and further reading
43
3
Dictionaries and tolerant retrieval
45
3.1
Search structures for dictionaries
45
3.2
Wildcard queries
48
3.3
Spelling correction
52
3.4
Phonetic correction
58
3.5
References and further reading
59
4
Index construction
61
4.1
Hardware basics
62
4.2
Blocked sort-based indexing
63
4.3
Single-pass in-memory indexing
66
4.4
Distributed indexing
68
4.5
Dynamic indexing
71
vj
Contents
4.6
Other types of indexes
73
4.7
References and further reading
76
5
Index compression
78
5.1
Statistical properties of terms in information retrieval
79
5.2
Dictionary compression
82
5.3
Postings file compression
87
5.4
References and further reading
97
6
Scoring, term weighting, and the vector space model
100
6.1
Parametric and zone indexes
101
6.2
Term frequency and weighting
107
6.3
The vector space model for scoring
110
6.4
Variant tf-idf functions
116
6.5
References and further reading
122
7
Computing scores in a complete search system
124
7.1
Efficient scoring and ranking
124
7.2
Components of an information retrieval system
132
7.3
Vector space scoring and query operator interaction
136
7.4
References and further reading
137
8
Evaluation in information retrieval
139
8.1
Information retrieval system evaluation
140
8.2
Standard test collections
141
8.3
Evaluation of unranked retrieval sets
142
8.4
Evaluation of ranked retrieval results
145
8.5
Assessing relevance
151
8.6
A broader perspective: System quality and user
utility
154
8.7
Results snippets
157
8.8
References and further reading
159
9
Relevance feedback and query expansion
162
9.1
Relevance feedback and
pseudo
relevance
feedback
163
9.2
Global methods for query reformulation
173
9.3
References and further reading
177
10
XML retrieval
178
10.1
Basic XML concepts
180
10.2
Challenges in XML retrieval
183
10.3
A vector space model for XML retrieval
188
10.4
Evaluation of XML retrieval
192
Contents
vii
10.5
Text-centric versus data-centric XML retrieval
196
10.6
References and further reading
198
22
Probabilistic information retrieval
201
11.1
Review of basic probability theory
202
11.2
The probability ranking principle
203
11.3
The binary independence model
204
11.4
An appraisal and some extensions
212
11.5
References and further reading
216
12
Language-models for information retrieval
218
12.1
Language models
218
12.2
The query likelihood model
223
12.3
Language modeling versus other approaches
in information retrieval
229
12.4
Extended language modeling approaches
230
12.5
References and further reading
232
13
Text classification and Naive
Bayes
234
13.1
The text classification problem
237
13.2
Naive
Bayes
text classification
238
13.3
The Bernoulli model
243
13.4
Properties of Naive
Bayes
245
13.5
Feature selection
251
13.6
Evaluation of text classification
258
13.7
References and further reading
264
24
Vector space classification
266
14.1
Document representations and measures of relatedness
in vector spaces
267
14.2
Rocchio
classification
269
14.3
к
nearest neighbor
273
14.4
Linear versus nonlinear classifiers
277
14.5
Classification with more than two classes
281
14.6
The bias-variance tradeoff
284
14.7
References and further reading
291
25
Support vector machines and machine learning on documents
293
15.1
Support vector machines: The linearly separable case
294
15.2
Extensions to the support vector machine model
300
15.3
Issues in the classification of text documents
307
15.4
Machine-learning methods in ad hoc information retrieval
314
15.5
References and further reading
318
viii Contents
16
Flat clustering
321
16.1
Clustering in information retrieval
322
16.2
Problem statement
326
16.3
Evaluation of clustering
327
16.4
К
-means
331
16.5
Model-based clustering
338
16.6
References and further reading
343
17
Hierarchical clustering
346
17.1
Hierarchical agglomerative clustering
347
17.2
Single-link and complete-link clustering
350
17.3
Group-average agglomerative clustering
356
17.4
Centroid clustering
358
17.5
Optimality of hierarchical agglomerative
clustering
360
17.6
Divisive clustering
362
17.7
Cluster labeling
363
17.8
Implementation notes
365
17.9
References and further reading
367
18
Matrix decompositions and latent semantic indexing
369
18.1
Linear algebra review
369
18.2
Term-document matrices and singular value
decompositions
373
18.3
Low-rank approximations
376
18.4
Latent semantic indexing
378
18.5
References and further reading
383
19
Web search basics
385
19.1
Background and history
385
19.2
Web characteristics
387
19.3
Advertising as the economic model
392
19.4
The search user experience
395
19.5
Index size and estimation
396
19.6
Near-duplicates and shingling
400
19.7
References and further reading
404
20
Web crawling and indexes
405
20.1
Overview
405
20.2
Crawling
406
20.3
Distributing indexes
415
20.4
Connectivity servers
416
20.5
References and further reading
419
Contents ix
21 Link
analysis All
21.1
The Web as a graph
422
21.2 PageRank 424
21.3
Hubs and authorities
433
21.4
References and further reading
439
Bibliography
441
Index
469
|
| adam_txt |
Contents
Table of
Notation
page
xi
Preface
xv
1
Boolean retrieval
1
1.1
An example information retrieval problem
3
1.2
A first take at building an inverted index
6
1.3
Processing Boolean queries
9
1.4
The extended Boolean model versus ranked retrieval
13
1.5
References and further reading
16
2
The term vocabulary ana postings lists
18
2.1
Document delineation and character sequence decoding
18
2.2
Determining the vocabulary of terms
21
2.3
Faster postings list intersection via skip pointers
33
2.4
Positional postings and phrase queries
36
2.5
References and further reading
43
3
Dictionaries and tolerant retrieval
45
3.1
Search structures for dictionaries
45
3.2
Wildcard queries
48
3.3
Spelling correction
52
3.4
Phonetic correction
58
3.5
References and further reading
59
4
Index construction
61
4.1
Hardware basics
62
4.2
Blocked sort-based indexing
63
4.3
Single-pass in-memory indexing
66
4.4
Distributed indexing
68
4.5
Dynamic indexing
71
vj
Contents
4.6
Other types of indexes
73
4.7
References and further reading
76
5
Index compression
78
5.1
Statistical properties of terms in information retrieval
79
5.2
Dictionary compression
82
5.3
Postings file compression
87
5.4
References and further reading
97
6
Scoring, term weighting, and the vector space model
100
6.1
Parametric and zone indexes
101
6.2
Term frequency and weighting
107
6.3
The vector space model for scoring
110
6.4
Variant tf-idf functions
116
6.5
References and further reading
122
7
Computing scores in a complete search system
124
7.1
Efficient scoring and ranking
124
7.2
Components of an information retrieval system
132
7.3
Vector space scoring and query operator interaction
136
7.4
References and further reading
137
8
Evaluation in information retrieval
139
8.1
Information retrieval system evaluation
140
8.2
Standard test collections
141
8.3
Evaluation of unranked retrieval sets
142
8.4
Evaluation of ranked retrieval results
145
8.5
Assessing relevance
151
8.6
A broader perspective: System quality and user
utility
154
8.7
Results snippets
157
8.8
References and further reading
159
9
Relevance feedback and query expansion
162
9.1
Relevance feedback and
pseudo
relevance
feedback
163
9.2
Global methods for query reformulation
173
9.3
References and further reading
177
10
XML retrieval
178
10.1
Basic XML concepts
180
10.2
Challenges in XML retrieval
183
10.3
A vector space model for XML retrieval
188
10.4
Evaluation of XML retrieval
192
Contents
vii
10.5
Text-centric versus data-centric XML retrieval
196
10.6
References and further reading
198
22
Probabilistic information retrieval
201
11.1
Review of basic probability theory
202
11.2
The probability ranking principle
203
11.3
The binary independence model
204
11.4
An appraisal and some extensions
212
11.5
References and further reading
216
12
Language-models for information retrieval
218
12.1
Language models
218
12.2
The query likelihood model
223
12.3
Language modeling versus other approaches
in information retrieval
229
12.4
Extended language modeling approaches
230
12.5
References and further reading
232
13
Text classification and Naive
Bayes
234
13.1
The text classification problem
237
13.2
Naive
Bayes
text classification
238
13.3
The Bernoulli model
243
13.4
Properties of Naive
Bayes
245
13.5
Feature selection
251
13.6
Evaluation of text classification
258
13.7
References and further reading
264
24
Vector space classification
266
14.1
Document representations and measures of relatedness
in vector spaces
267
14.2
Rocchio
classification
269
14.3
к
nearest neighbor
273
14.4
Linear versus nonlinear classifiers
277
14.5
Classification with more than two classes
281
14.6
The bias-variance tradeoff
284
14.7
References and further reading
291
25
Support vector machines and machine learning on documents
293
15.1
Support vector machines: The linearly separable case
294
15.2
Extensions to the support vector machine model
300
15.3
Issues in the classification of text documents
307
15.4
Machine-learning methods in ad hoc information retrieval
314
15.5
References and further reading
318
viii Contents
16
Flat clustering
321
16.1
Clustering in information retrieval
322
16.2
Problem statement
326
16.3
Evaluation of clustering
327
16.4
К
-means
331
16.5
Model-based clustering
338
16.6
References and further reading
343
17
Hierarchical clustering
346
17.1
Hierarchical agglomerative clustering
347
17.2
Single-link and complete-link clustering
350
17.3
Group-average agglomerative clustering
356
17.4
Centroid clustering
358
17.5
Optimality of hierarchical agglomerative
clustering
360
17.6
Divisive clustering
362
17.7
Cluster labeling
363
17.8
Implementation notes
365
17.9
References and further reading
367
18
Matrix decompositions and latent semantic indexing
369
18.1
Linear algebra review
369
18.2
Term-document matrices and singular value
decompositions
373
18.3
Low-rank approximations
376
18.4
Latent semantic indexing
378
18.5
References and further reading
383
19
Web search basics
385
19.1
Background and history
385
19.2
Web characteristics
387
19.3
Advertising as the economic model
392
19.4
The search user experience
395
19.5
Index size and estimation
396
19.6
Near-duplicates and shingling
400
19.7
References and further reading
404
20
Web crawling and indexes
405
20.1
Overview
405
20.2
Crawling
406
20.3
Distributing indexes
415
20.4
Connectivity servers
416
20.5
References and further reading
419
Contents ix
21 Link
analysis All
21.1
The Web as a graph
422
21.2 PageRank 424
21.3
Hubs and authorities
433
21.4
References and further reading
439
Bibliography
441
Index
469 |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author | Manning, Christopher D. 1965- |
| author_GND | (DE-588)172764629 (DE-588)136257062 (DE-588)112281672 |
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| author_sort | Manning, Christopher D. 1965- |
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| dewey-full | 025.04 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 025 - Operations of libraries and archives |
| dewey-raw | 025.04 |
| dewey-search | 025.04 |
| dewey-sort | 225.04 |
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| discipline | Allgemeines Informatik |
| discipline_str_mv | Allgemeines Informatik |
| edition | 1. publ. |
| format | Book |
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| genre | (DE-588)4151278-9 Einführung gnd-content |
| genre_facet | Einführung |
| id | DE-604.BV035104872 |
| illustrated | Illustrated |
| index_date | 2024-07-02T22:15:31Z |
| indexdate | 2024-07-09T21:22:19Z |
| institution | BVB |
| isbn | 9780521865715 0521865719 |
| language | English |
| lccn | 2008001257 |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-016772797 |
| oclc_num | 232365569 |
| open_access_boolean | 1 |
| owner | DE-355 DE-BY-UBR DE-91G DE-BY-TUM DE-29T DE-19 DE-BY-UBM DE-706 DE-12 DE-20 DE-92 DE-11 DE-525 DE-188 DE-634 DE-473 DE-BY-UBG DE-29 DE-384 DE-858 |
| owner_facet | DE-355 DE-BY-UBR DE-91G DE-BY-TUM DE-29T DE-19 DE-BY-UBM DE-706 DE-12 DE-20 DE-92 DE-11 DE-525 DE-188 DE-634 DE-473 DE-BY-UBG DE-29 DE-384 DE-858 |
| physical | XXI, 482 S. graph. Darst. |
| psigel | ebook |
| publishDate | 2008 |
| publishDateSearch | 2008 |
| publishDateSort | 2008 |
| publisher | Cambridge Univ. Press |
| record_format | marc |
| spelling | Manning, Christopher D. 1965- Verfasser (DE-588)172764629 aut Introduction to information retrieval Christopher D. Manning ; Prabhakar Raghavan ; Hinrich Schütze 1. publ. Cambridge [u.a.] Cambridge Univ. Press 2008 XXI, 482 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Hier auch später erschienene, unveränderte Nachdrucke Text processing (Computer science) Information retrieval Document clustering Semantic Web Abfrageverarbeitung (DE-588)4378490-2 gnd rswk-swf Semantic Web (DE-588)4688372-1 gnd rswk-swf Textverarbeitung (DE-588)4059667-9 gnd rswk-swf Dokumentverarbeitung (DE-588)4234488-8 gnd rswk-swf Information Retrieval (DE-588)4072803-1 gnd rswk-swf (DE-588)4151278-9 Einführung gnd-content Information Retrieval (DE-588)4072803-1 s Semantic Web (DE-588)4688372-1 s Textverarbeitung (DE-588)4059667-9 s Abfrageverarbeitung (DE-588)4378490-2 s DE-604 Dokumentverarbeitung (DE-588)4234488-8 s 1\p DE-604 Raghavan, Prabhakar Sonstige (DE-588)136257062 oth Schütze, Hinrich Sonstige (DE-588)112281672 oth http://nlp.stanford.edu/IR-book/pdf/irbookonlinereading.pdf kostenfrei Volltext http://www.loc.gov/catdir/enhancements/fy0810/2008001257-d.html Publisher description Digitalisierung UB Regensburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016772797&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Manning, Christopher D. 1965- Introduction to information retrieval Text processing (Computer science) Information retrieval Document clustering Semantic Web Abfrageverarbeitung (DE-588)4378490-2 gnd Semantic Web (DE-588)4688372-1 gnd Textverarbeitung (DE-588)4059667-9 gnd Dokumentverarbeitung (DE-588)4234488-8 gnd Information Retrieval (DE-588)4072803-1 gnd |
| subject_GND | (DE-588)4378490-2 (DE-588)4688372-1 (DE-588)4059667-9 (DE-588)4234488-8 (DE-588)4072803-1 (DE-588)4151278-9 |
| title | Introduction to information retrieval |
| title_auth | Introduction to information retrieval |
| title_exact_search | Introduction to information retrieval |
| title_exact_search_txtP | Introduction to information retrieval |
| title_full | Introduction to information retrieval Christopher D. Manning ; Prabhakar Raghavan ; Hinrich Schütze |
| title_fullStr | Introduction to information retrieval Christopher D. Manning ; Prabhakar Raghavan ; Hinrich Schütze |
| title_full_unstemmed | Introduction to information retrieval Christopher D. Manning ; Prabhakar Raghavan ; Hinrich Schütze |
| title_short | Introduction to information retrieval |
| title_sort | introduction to information retrieval |
| topic | Text processing (Computer science) Information retrieval Document clustering Semantic Web Abfrageverarbeitung (DE-588)4378490-2 gnd Semantic Web (DE-588)4688372-1 gnd Textverarbeitung (DE-588)4059667-9 gnd Dokumentverarbeitung (DE-588)4234488-8 gnd Information Retrieval (DE-588)4072803-1 gnd |
| topic_facet | Text processing (Computer science) Information retrieval Document clustering Semantic Web Abfrageverarbeitung Textverarbeitung Dokumentverarbeitung Information Retrieval Einführung |
| url | http://nlp.stanford.edu/IR-book/pdf/irbookonlinereading.pdf http://www.loc.gov/catdir/enhancements/fy0810/2008001257-d.html http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016772797&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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