Information retrieval: implementing and evaluating search engines
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cambridge, MA [u.a.]
MIT Press
2010
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis Klappentext |
| Beschreibung: | Hier auch später erschienene, unveränderte Nachdrucke |
| Beschreibung: | XXIV, 606 S. Ill., graph. Darst. |
| ISBN: | 9780262026512 9780262528870 |
Internformat
MARC
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| 100 | 1 | |a Büttcher, Stefan |d 1978- |e Verfasser |0 (DE-588)1095262041 |4 aut | |
| 245 | 1 | 0 | |a Information retrieval |b implementing and evaluating search engines |c Stefan Büttcher ; Charles L. A. Clarke ; Gordon V. Cormack |
| 264 | 1 | |a Cambridge, MA [u.a.] |b MIT Press |c 2010 | |
| 300 | |a XXIV, 606 S. |b Ill., 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 Search engines |x Programming | |
| 650 | 4 | |a Information retrieval | |
| 650 | 0 | 7 | |a Programmierung |0 (DE-588)4076370-5 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Information Retrieval |0 (DE-588)4072803-1 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Suchmaschine |0 (DE-588)4423007-2 |2 gnd |9 rswk-swf |
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| 689 | 0 | 2 | |a Information Retrieval |0 (DE-588)4072803-1 |D s |
| 689 | 0 | |5 DE-604 | |
| 700 | 1 | |a Clarke, Charles L. A. |d 1964- |e Verfasser |0 (DE-588)142311588 |4 aut | |
| 700 | 1 | |a Cormack, Gordon V. |e Verfasser |0 (DE-588)142347647 |4 aut | |
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| 856 | 4 | 2 | |m Digitalisierung UB Passau - ADAM Catalogue Enrichment |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020575680&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |3 Klappentext |
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Datensatz im Suchindex
| _version_ | 1804143274589421568 |
|---|---|
| adam_text | Contents
Foreword
xix
Preface
xxi
Notation
xxv
Foundations
1
Introduction
2
1.1
What Is Information Retrieval?
2
1.1.1
Web Search
2
1.1.2
Other Search Applications
3
1.1.3
Other
IR
Applications
Ą
1.2
Information Retrieval Systems
5
1.2.1
Basic
IR
System Architecture
5
1.2.2
Documents and Update
7
1.2.3
Performance Evaluation
8
1.3
Working with Electronic Text
£>
1.3.1
Text Formats
9
1.3.2
A Simple Tokenization of English Text
13
1.3.3
Term Distributions
15
1.3.4
Language Modeling
11
1.4
Test Collections
23
1.4.1
TREC
Tasks ^
1.5
Open-Source
IR
Systems
27
1.5.1
Lucene
27
1.5.2
Indri
27
1.5.3
Wumpus £S
Contents
1.6
Further Reading
28
1.7
Exercises
30
1.8
Bibliography
32
Basic Techniques
33
2.1
Inverted Indices
S3
2.1.1
Extended Example: Phrase Search
35
2.1.2
Implementing Inverted Indices
39
2.1.3
Documents and Other Elements
Ą5
2.2
Retrieval and Ranking
51
2.2.1
The Vector Space Model
5Ą
2.2.2
Proximity Ranking
60
2.2.3
Boolean Retrieval
63
2.3
Evaluation
66
2.3.1
Recall and Precision
67
2.3.2
Effectiveness Measures for Ranked Retrieval
68
2.3.3
Building a Test Collection
13
2.3.4
Efficiency Measures
15
2.4
Summary
16
2.5
Further Reading
77
2.6
Exercises
79
2.7
Bibliography
82
Tokens and Terms
8Ą
3.1
English
85
3.1.1
Punctuation and Capitalization
55
3.1.2
Stemming
86
3.1.3
Stopping
£0
3.2
Characters
91
3.3
Character N-Grams
92
3.4
European Languages
9Ą
3.5
CJK Languages
55
3.6
Further Reading
91
3.7
Exercises
99
3.8
Bibliography
100
Contents
II Indexing
103
Static Inverted Indices
10Ą
4.1
Index Components and Index Life Cycle
10Ą
4.2
The Dictionary
106
4.3
Postings Lists
110
AA Interleaving Dictionary and Postings Lists
11Ą
4.5
Index Construction
118
4.5.1
In-Memory Index Construction
119
4.5.2
Sort-Based Index Construction
125
4.5.3
Merge-Based Index Construction
127
4.6
Other Types of Indices
131
4.7
Summary
132
4.8
Further Reading
132
4.9
Exercises
133
4.10
Bibliography
135
Query Processing
137
5.1
Query Processing for Ranked Retrieval
137
5.1.1
Document-at-a-Time Query Processing
139
5.1.2
Term-at-a-Time Query Processing
1Ą5
5.1.3
Precomputing Score Contributions
151
5.1.4
Impact Ordering
153
5.1.5
Static Index Pruning
153
5.2
Lightweight Structure
160
5.2.1
Generalized Concordance Lists
160
5.2.2
Operators
162
5.2.3
Examples
163
5.2.4
Implementation
165
5.3
Further Reading
169
5.4
Exercises
170
5.5
Bibliography
171
Contents
Index
Compression
174
6.1
General-Purpose Data Compression
175
6.2 Symbolwise Data
Compression
176
6.2.1
Modeling and Coding
177
6.2.2
Huffman Coding
181
6.2.3
Arithmetic Coding
186
6.2.4
Symbolwise Text Compression
189
6.3
Compressing Postings Lists
191
6.3.1
Nonparametric Gap Compression
192
6.3.2
Parametric Gap Compression
195
6.3.3
Context-Aware Compression Methods
201
6.3.4
Index Compression for High Query Performance
20Ą
6.3.5
Compression Effectiveness
209
6.3.6
Decoding Performance
212
6.3.7
Document Reordering
214
6.4
Compressing the Dictionary
216
6.5
Summary
222
6.6
Further Reading
223
6.7
Exercises
224
6.8
Bibliography
225
Dynamic Inverted Indices
228
7.1
Batch Updates
229
7.2
Incremental Index Updates
231
7.2.1
Contiguous Inverted Lists
233
7.2.2
Noncontiguous Inverted Lists
239
7.3
Document Deletions
243
7.3.1
Invalidation List
24З
7.3.2
Garbage Collection
245
7.4
Document Modifications
250
7.5
Discussion and Further Reading
251
7.6
Exercises
253
7.7
Bibliography
254
Contents
III Retrieval and Ranking
257
Probabilistic Retrieval
258
8.1
Modeling Relevance
259
8.2
The Binary Independence Model
261
8.3
The
Robertson/Spärck
Jones Weighting Formula
26Ą
8.4
Term Frequency
266
8.4.1
Bookstein s Two-Poisson Model
267
8.4.2
Approximating the Two-Poisson Model
270
8.4.3
Query Term Frequency
271
8.5
Document Length: BM25
271
8.6
Relevance Feedback
273
8.6.1
Term Selection
27Ą
8.6.2
Pseudo-Relevance Feedback
275
8.7
Field Weights: BM25F
277
8.8
Experimental Comparison
279
8.9
Further Reading
280
8.10
Exercises
281
8.11
Bibliography
282
Language Modeling and Related Methods
286
9.1
Generating Queries from Documents
287
9.2
Language Models and Smoothing
289
9.3
Ranking with Language Models
292
9.4
Kullback-Leibler Divergence
296
9.5
Divergence from Randomness
298
9.5.1
A Model of Randomness
299
9.5.2
Eliteness
301
9.5.3
Document Length Normalization
301
9.6
Passage Retrieval and Ranking
302
9.6.1
Passage Scoring
30Ą
9.6.2
Implementation
30Ą
9.7
Experimental Comparison
306
9.8
Further Reading
306
Contents
9.9
Exercises
307
9.10
Bibliography
301
10
Categorization and Filtering
310
10.1
Detailed Examples
313
10.1.1
Topic-Oriented Batch Filtering
313
10.1.2
On-Line Filtering
311
10.1.3
Learning from Historical Examples
318
10.1.4
Language Categorization
320
10.1.5
On-Line Adaptive Spam Filtering
325
10.1.6
Threshold Choice for Binary Categorization
329
10.2
Classification
331
10.2.1
Odds and Odds Ratios
333
10.2.2
Building Classifiers
33Ą
10.2.3
Learning Modes
336
10.2.4
Feature Engineering
338
10.3
Probabilistic Classifiers
339
10.3.1
Probability Estimates
3Ą0
10.3.2
Combining Probability Estimates
3Ą3
10.3.3
Practical Considerations
3Ą1
10.4
Linear Classifiers
3Ą9
10.4.1
Perceptron Algorithm
352
10.4.2
Support Vector Machines
353
10.5
Similarity-Based Classifiers
55^
10.5.1
Rocchio s Method
35Ą
10.5.2
Memory-Based Methods
355
10.6
Generalized Linear Models
355
10.6.1
Kernel Methods
557
10.7
Information-Theoretic Models
359
10.7.1
Comparing Models
360
10.7.2
Sequential Compression Models
361
10.7.3
Decision Trees and Stumps
36Ą
10.8
Experimental Comparison
366
10.8.1
Topic-Oriented On-Line Filtering
361
10.8.2
On-Line Adaptive Spam Filtering
369
10.9
Further Reading
311
Contents
10.10
Exercises
372
10.11
Bibliography
373
11
Fusion and Metalearning
376
11.1
Search-Result Fusion
577
11.1.1
Fixed-Cutoff Aggregation
379
11.1.2
Rank and Score Aggregation
380
11.2
Stacking Adaptive Filters
381
11.3
Stacking Batch Classifiers
383
11.3.1
Holdout Validation
383
11.3.2
Cross-Validation
38Ą
11.4
Bagging
11.5
Boosting
11.6
Multicategory Ranking and Classification
388
11.6.1
Document Versus Category Scores
389
11.6.2
Document Versus Category Rank Fusion
390
11.6.3
Multicategory Methods
391
11.7
Learning to Rank
39
Ą
11.7.1
What Is Learning to Rank?
395
11.7.2
Learning-to-Rank Methods
396
11.7.3
What to Optimize?
396
11.7.4
Learning to Rank for Categorization
397
11.7.5
Learning for Ranked
IR
398
11.7.6
The
LETOR
Data Set
399
11.8
Further Reading
Ą00
11.9
Exercises
.¿oi
11.10
Bibliography
Ą01
IV Evaluation
Ą05
12
Measuring Effectiveness
Ą06
12.1
Traditional Effectiveness Measures
Ą07
12.1.1
Recall and Precision
^07
12.1.2
Precision at
к
Documents (P@fc)
Ą08
12.1.3
Average Precision (AP)
Contents
15.3.3
Properties of Page-Rank
528
15.3.4
Other Link Analysis Methods: HITS and SALSA
532
15.3.5
Other Static Ranking Methods
535
15.4
Dynamic Ranking
535
15.4.1
Anchor Text
536
15.4.2
Novelty
537
15.5
Evaluating Web Search
538
15.5.1
Named Page Finding
538
15.5.2
Implicit User Feedback
5Ą0
15.6
Web Crawlers
5Ą1
15.6.1
Components of a Crawler
5Ą2
15.6.2
Crawl Order
5Ą1
15.6.3
Duplicates and Near-Duplicates
5Ą9
15.7
Summary
553
15.8
Further Reading
553
15.8.1
Link Analysis
554
15.8.2
Anchor Text
555
15.8.3
Implicit Feedback
555
15.8.4
Web Crawlers
556
15.9
Exercises
556
15.10
Bibliography
558
16
XML Retrieval
564
16.1
The Essence of XML
565
16.1.1
Document Type Definitions
568
16.1.2
XML Schema
570
16.2
Paths, Trees, and FLWORs
571
16.2.1
XPath
571
16.2.2
NEXI
572
16.2.3
XQuery
574
16.3
Indexing and Query Processing
576
16.4
Ranked Retrieval
579
16.4.1
Ranking Elements
580
16.4.2
Overlapping Elements
582
16.4.3
Retrievable Elements
583
16.5
Evaluation
583
Contents
16.5.1 Test
Collections
583
16.5.2
Effectiveness Measures
58Ą
16.6
Further Reading
585
16.7
Exercises
587
16.8
Bibliography
587
VI Appendix
591
Computer Performance
592
A.I Sequential Versus Random Access on Disk
592
A.
2
Sequential Versus Random Access in RAM
593
A.3 Pipelined Execution and Branch Prediction
59Ą
Index
597
Information retrieval is the foundation for modern search engines. This textbook offers an introduction
tö
the core topics underlying modern search technologies, including algorithms, data structures, indexing;
retrieval, and evaluation. The emphasis is on implementation and experimentation; each chapter includes
exercises and suggestions for student projects. Wumpus-a multiuser open-source information retrieval
system developed by one of the authors and available online-provides model implementations and a basis
for student work. The modular structure of the book allows instructors to use it in a variety of graduate-level
courses, including courses taught from a database systems perspective, traditional information retrieval
courses with a focus on
IR
theory, and courses covering the basics of Web retrieval.
After an introduction to the basics of information retrieval, the text covers three major topic areas-
indexing, retrieval, and evaluation—in self-contained parts. The final part of the book draws on and extends
the
generai
material in the earlier parts, treating such specific applications as parallel search engines, Web
search, and XML retrieval. End-of-chapter references point to further reading; exercises range from pencil·
and-paper problems to substantial programming projects. In addition to its classroom use,
Information
Retrieval will be a valuable reference for professionals In computer science, computer engineer
software engineering.
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|
| any_adam_object | 1 |
| author | Büttcher, Stefan 1978- Clarke, Charles L. A. 1964- Cormack, Gordon V. |
| author_GND | (DE-588)1095262041 (DE-588)142311588 (DE-588)142347647 |
| author_facet | Büttcher, Stefan 1978- Clarke, Charles L. A. 1964- Cormack, Gordon V. |
| author_role | aut aut aut |
| author_sort | Büttcher, Stefan 1978- |
| author_variant | s b sb c l a c cla clac g v c gv gvc |
| building | Verbundindex |
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| callnumber-label | TK5105 |
| callnumber-raw | TK5105.884 |
| callnumber-search | TK5105.884 |
| callnumber-sort | TK 45105.884 |
| callnumber-subject | TK - Electrical and Nuclear Engineering |
| classification_rvk | AN 95000 ST 205 ST 252 ST 270 |
| ctrlnum | (OCoLC)699679128 (DE-599)BVBBV036656272 |
| dewey-full | 025.5/24 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 025 - Operations of libraries and archives |
| dewey-raw | 025.5/24 |
| dewey-search | 025.5/24 |
| dewey-sort | 225.5 224 |
| dewey-tens | 020 - Library and information sciences |
| discipline | Allgemeines Informatik |
| format | Book |
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| id | DE-604.BV036656272 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T22:45:04Z |
| institution | BVB |
| isbn | 9780262026512 9780262528870 |
| language | English |
| lccn | 2009048455 |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-020575680 |
| oclc_num | 699679128 |
| open_access_boolean | |
| owner | DE-2070s DE-473 DE-BY-UBG DE-12 DE-634 DE-20 DE-11 DE-573 DE-355 DE-BY-UBR DE-384 DE-739 DE-29 DE-29T DE-188 |
| owner_facet | DE-2070s DE-473 DE-BY-UBG DE-12 DE-634 DE-20 DE-11 DE-573 DE-355 DE-BY-UBR DE-384 DE-739 DE-29 DE-29T DE-188 |
| physical | XXIV, 606 S. Ill., graph. Darst. |
| publishDate | 2010 |
| publishDateSearch | 2010 |
| publishDateSort | 2010 |
| publisher | MIT Press |
| record_format | marc |
| spelling | Büttcher, Stefan 1978- Verfasser (DE-588)1095262041 aut Information retrieval implementing and evaluating search engines Stefan Büttcher ; Charles L. A. Clarke ; Gordon V. Cormack Cambridge, MA [u.a.] MIT Press 2010 XXIV, 606 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Hier auch später erschienene, unveränderte Nachdrucke Search engines Programming Information retrieval Programmierung (DE-588)4076370-5 gnd rswk-swf Information Retrieval (DE-588)4072803-1 gnd rswk-swf Suchmaschine (DE-588)4423007-2 gnd rswk-swf Suchmaschine (DE-588)4423007-2 s Programmierung (DE-588)4076370-5 s Information Retrieval (DE-588)4072803-1 s DE-604 Clarke, Charles L. A. 1964- Verfasser (DE-588)142311588 aut Cormack, Gordon V. Verfasser (DE-588)142347647 aut Digitalisierung UB Bamberg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020575680&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020575680&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext |
| spellingShingle | Büttcher, Stefan 1978- Clarke, Charles L. A. 1964- Cormack, Gordon V. Information retrieval implementing and evaluating search engines Search engines Programming Information retrieval Programmierung (DE-588)4076370-5 gnd Information Retrieval (DE-588)4072803-1 gnd Suchmaschine (DE-588)4423007-2 gnd |
| subject_GND | (DE-588)4076370-5 (DE-588)4072803-1 (DE-588)4423007-2 |
| title | Information retrieval implementing and evaluating search engines |
| title_auth | Information retrieval implementing and evaluating search engines |
| title_exact_search | Information retrieval implementing and evaluating search engines |
| title_full | Information retrieval implementing and evaluating search engines Stefan Büttcher ; Charles L. A. Clarke ; Gordon V. Cormack |
| title_fullStr | Information retrieval implementing and evaluating search engines Stefan Büttcher ; Charles L. A. Clarke ; Gordon V. Cormack |
| title_full_unstemmed | Information retrieval implementing and evaluating search engines Stefan Büttcher ; Charles L. A. Clarke ; Gordon V. Cormack |
| title_short | Information retrieval |
| title_sort | information retrieval implementing and evaluating search engines |
| title_sub | implementing and evaluating search engines |
| topic | Search engines Programming Information retrieval Programmierung (DE-588)4076370-5 gnd Information Retrieval (DE-588)4072803-1 gnd Suchmaschine (DE-588)4423007-2 gnd |
| topic_facet | Search engines Programming Information retrieval Programmierung Information Retrieval Suchmaschine |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020575680&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020575680&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
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