Verfügbarkeit: Search engines

Search engines: information retrieval in practice

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Bibliographische Detailangaben
Hauptverfasser:	Croft, W. Bruce 1952- (VerfasserIn), Metzler, Donald (VerfasserIn), Strohman, Trevor (VerfasserIn)
Format:	Buch
Sprache:	English
Veröffentlicht:	Boston ; Munich [u.a.] Pearson 2009
Ausgabe:	internat. ed.
Schlagworte:	Information retrieval Information storage and retrieval systems Search engines Suchmaschine Information Retrieval Lehrbuch
Online-Zugang:	Inhaltsverzeichnis
Beschreibung:	Hier auch später erschienene, unveränderte Nachdrucke
Beschreibung:	XXV, 524 S. Ill.
ISBN:	9780131364899 0131364898

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Datensatz im Suchindex

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adam_text	Contents 1 Search Engines and Information Retrieval ....................... 1 1.1 What Is Information Retrieval?. ............................. 1 1.2 The Big issues ............................................. 4 1.3 Search Engines ............................................ 6 1.4 Search Engineers .......................................... 9 2 Architecture of a Search Engine ................................. 13 2.1 What Ь an Architecture? ...............................___ 13 2.2 Bask Building Blocks ...................................... 14 2.3 Breaking It Down ......................................... 17 2.3.1 Text Acquisition. .................................... 17 2.3.2 Text Transformation ................................. 19 2.3.3 IndexCreation ...................................... 22 2.3.4 User Interaction ..................................... 23 2.3.5 Ranking ............................................ 25 2.3.6 Evaluation .......................................... 27 2.4 How Does It Radfy Work? .................................. 28 3 Crawls and Feeds .............................................. 31 3.1 Deciding What to Search ................................... 31 3.2 CrawlingtheWeb ......................................... 32 3.2.1 Retrieving Web Pages ................................ 33 3.2.2 The Web Crawler .................................... 35 3.2.3 Freshness ........................................... 37 3.2.4 Focused Crawling ................................... 41 3.2.5 DeepWeb .......................................... 41 X Contents 3.2.6 Sitemaps........................................... 43 3.2.7 Distributed Crawling ................................ 44 3.3 Crawling Documents and Email ----......................... 46 3.4 Document Feeds .......................................... 47 3.5 The Conversion Problem ................................... 49 3.5.1 Character Encodings ................................. 50 3.6 Storing the Documents ..................................... 52 3.6.1 Using a Database System ..............___............ 53 3.6.2 Random Access ..................................... 53 3.6.3 Compression and Large Files .......................... 54 3.6.4 Update....... ...................................... 56 3.6.5 BigTable ............................................ 57 3.7 Detecting Duplicates ...................................... 60 3.8 Removing Noise ........................................... 63 4 Processing Text ............................................... 75 4.1 From Words to Terms ...................................... 75 4.2 Text Statistics ............................................. 77 4.2.1 Vocabulary Growth .................................. 82 4.2.2 Estimating Collection and Result Set Sizes .............. 85 4.3 Document Parsing ......................................... 88 4.3.1 Overview. .........................................· 88 4.3.2 Tokenizing.. ....................................... 89 4.3.3 Stopping ........................................... 92 4.3.4 Stemming .......................................... 93 4.3.5 Phrases and N-grams ................................. 99 4.4 Document Structure and Markup ........................----- W3 4.5 Link Analysis ............................................. 106 4.5.1 Anchor Text ........................................ 107 4.5.2 PageRank .......................................... 107 4.5.3 Link Quality ........................................ Ш 4.6 Information Extraction ..................................... 115 4.6.1 Hidden Markov Models for Extraction ................. 117 4.7 Internationalization ........................................ 120 Contents XI 5 Ranking with Indexes .......................................... 127 5.1 Overview ................................................. 127 5.2 Abstract Model of Ranking ................................. 128 5.3 Inverted Indexes ........................................... 131 5.3.1 Documents ......................................... 133 5.3.2 Counts ............................................. 135 5.3.3 Positions ........................................... 136 5.3.4 Fields and Extents .................................... 138 5.3.5 Scores .............................................. 140 5.3.6 Ordering ........................................... 141 5.4 Compression ............................................. 142 5.4.1 Entropy and Ambiguity .............................. 144 5.4.2 Delta Encoding ..................................... 146 5.4.3 Bit-Aligned Codes ................................... 147 5.4.4 Byte-Aligned Codes ................................. 150 5.4.5 Compression in Practice .............................. 151 5.4.6 LookingAhead ...................................... 153 5.4.7 Skipping and Skip Pointers ........................... 153 5.5 Auxiliary Structures ........................................ 156 5.6 Index Construction ........................................ 158 5.6.1 Simple Construction ................................. 158 5.6.2 Merging ............................................ 159 5.6.3 Parallelism and Distribution .......................... 160 5.6.4 Update ............................................. 166 5.7 Query Processing .......................................... 167 5.7.1 Doœment-at-a-time Evaluation ....................... 168 5.7.2 Term-at-a-time Evaluation ............................ 170 5.7.3 Optimization Techniques ............................. 172 5.7.4 Structured Queries .................................. 180 5.7.5 Distributed Evaluation ............................... 182 5.7.6 Caching ............................................ 183 6 Queries and Interfaces ___..............___................... 191 6.1 Information Needs and Queries .........................-----191 6.2 Query Transformation and Refinement ....................... 194 6.2.1 Stopping and Stemming Revisited ..................... 194 6.2.2 Spell Checking and Suggestions ....................... 197 XII Contents 6.2.3 Query Expansion .................................... 203 6.2.4 Relevance Feedback .................................. 212 6.2.5 Context and Personaiization .......................... 215 6.3 ShowingtheResults ....................................... 219 6.3.1 Result Pages and Snippets ............................ 219 6.3.2 Advertising and Search ............................... 222 6.3.3 Clustering the Results ................................ 225 6.4 Cross-Language Search ..................................... 230 7 Retrieval Models ..........................................----- 237 7.1 Overview of Retrieval Models ............................... 237 7.1.1 Boolean Retrieval .................................... 239 7.1.2 The Vector Space Model .............................. 241 7.2 Probabilistic Models ....................................... 247 7.2.1 Information Retrieval as Classification ................. 248 7.2.2 The BM25 Ranking Algorithm ........................ 254 7.3 Ranking Based on Language Models ......................... 256 7.3.1 Query Likelihood Ranking .......................----- 258 7.3.2 Relevance Models and Pseudo-Relevance Feedback ...... 265 7.4 Complex Queries and Combining Evidence ___............... 271 7.4.1 The Inference Network Model ........................ 272 7.4.2 The Galago Query Language .......................... 277 7.5 WebSearch ............................................... 283 7.6 Machine Learning and Information Retrieval ___.............. 287 7.6.1 Learning to Rank .................................... 288 7.6.2 Topic Models and Vocabulary Mismatch ................ 292 7.7 Application-Based Models .................................. 295 8 Evaluating Search Engines ...................................... 301 8.1 Why Evaluate? ............................................ 301 8.2 The Evaluation Corpus ..............................,...... 303 8.3 Logging .................................................. 309 8.4 Effectiveness Metrics ....................................... 312 8.4.1 Recall and Precision ................................. 312 8.4.2 Averaging and Interpolation .......................... 317 8.4.3 Focusing on the Top Documents ...................... 322 8.4.4 Using Preferences .................................... 325 Contents XIII 8.5 Efficiency Metrics .........................................326 8.6 Training, Testing, and Statistics .............................. 329 8.6.1 Significance Tests .................................... 329 8.6.2 Setting Parameter Values ............................. 334 8.6.3 Online Testing ...................................... 336 8.7 The Bottom Line .......................................... 337 9 Classification and Clustering ...................................343 9.1 Classification and Categorization ............................344 9.1.1 Naïve Bayes ......................................... 346 9.1.2 Support Vector Machines ............................. 355 9.1.3 Evaluation .......................................... 363 9.1.4 Classifier and Feature Selection ........................ 363 9.1.5 Spam, Sentiment, and Online Advertising .............. 368 9.2 Clustering ................................................ 377 9.2.1 Hierarchical and Ä^Means Clustering ..................379 9.2.2 К Nearest Neighbor Clustering .......................388 9.2.3 Evaluation ..........................................390 9.2.4 HowtoChooseiv ...................................391 9.2.5 Clustering and Search ................................393 10 Social Search .................................................401 10.1 What Is Social Search? .....................................401 10.2 User Tags and Manual Indexing .............................404 10.2.1 Searching Tags ......................................406 10.2.2 Inferring Missing Tags ................................408 10.2.3 Browsing and Tag Clouds .............................410 10.3 Searchingwith Communities ...........................-----412 10.3.1 What Is a Community? ..............................412 10.3.2 Finding Communities ................................413 10.3.3 Community-Based Question Answering ................ 419 10.3.4 Collaborative Searching ..............................424 10.4 Filtering and Recommending ............................... 427 10.4.1 Document Filtering ..................................427 10.4.2 Collaborative Filtering ...............................436 10.5 Peer-to-PeerandMetasearch ................................442 10.5Л Distributed Search ...................................442 XIV Contents 10.5.2 P2PNetworb ......................................446 11 Beyond Bag of Words ..........................................455 1 LI Overview .................................................455 11.2 Feature-Based Retrieval Models .............................456 11.3 Term Dependence Models ..................................458 11.4 Structure Revisited ........................................463 11.4.1 XML Retrieval ...................................... 465 11.4.2 Entity Search ....................................... 468 11.5 Longer Questions, Better Answers ........................... 470 11.6 Words, Pictures, and Music ................................. 474 11.7 One Search Fits All? ....................................... 483 References ........................................................491 Index ............................................................ 517
any_adam_object	1
author	Croft, W. Bruce 1952- Metzler, Donald Strohman, Trevor
author_GND	(DE-588)137756658 (DE-588)138148090
author_facet	Croft, W. Bruce 1952- Metzler, Donald Strohman, Trevor
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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
dewey-tens	020 - Library and information sciences
discipline	Allgemeines Informatik
edition	internat. ed.
format	Book
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spellingShingle	Croft, W. Bruce 1952- Metzler, Donald Strohman, Trevor Search engines information retrieval in practice Information retrieval Information storage and retrieval systems Search engines Suchmaschine (DE-588)4423007-2 gnd Information Retrieval (DE-588)4072803-1 gnd
subject_GND	(DE-588)4423007-2 (DE-588)4072803-1 (DE-588)4123623-3
title	Search engines information retrieval in practice
title_auth	Search engines information retrieval in practice
title_exact_search	Search engines information retrieval in practice
title_full	Search engines information retrieval in practice W. Bruce Croft ; Donald Metzler ; Trevor Strohman
title_fullStr	Search engines information retrieval in practice W. Bruce Croft ; Donald Metzler ; Trevor Strohman
title_full_unstemmed	Search engines information retrieval in practice W. Bruce Croft ; Donald Metzler ; Trevor Strohman
title_short	Search engines
title_sort	search engines information retrieval in practice
title_sub	information retrieval in practice
topic	Information retrieval Information storage and retrieval systems Search engines Suchmaschine (DE-588)4423007-2 gnd Information Retrieval (DE-588)4072803-1 gnd
topic_facet	Information retrieval Information storage and retrieval systems Search engines Suchmaschine Information Retrieval Lehrbuch
url	http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017362908&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
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