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Marmanis H., Babenko D. — Algorithms of the intelligent web
Marmanis H., Babenko D. — Algorithms of the intelligent web



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Название: Algorithms of the intelligent web

Авторы: Marmanis H., Babenko D.

Аннотация:

Modern web application hype revolves around a rich UI experience. A lesser-known aspect of modern applications is the use of techniques that enable the intelligent processing of information and add value that can't be delivered by other means. Examples of success stories based on these techniques abound, and include household names such as Google, Netflix, and Amazon. This book describes how to build the algorithms that form the core of intelligence in these applications.
The book covers five important categories of algorithms: search, recommendations, groupings, classification, and the combination of classifiers. A separate book could be written on each of these topics, and clearly exhaustive coverage isn't a goal of this book. This book is an introduction to the fundamentals of these five topics. It's an attempt to present the basic algorithms of intelligent applications rather than an attempt to cover completely all algorithms of computational intelligence. The book is written for the widest audience possible and relies on a minimum of prerequisite knowledge.


Язык: en

Рубрика: Computer science/

Серия: Сделано в холле

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Год издания: 2009

Количество страниц: 345

Добавлена в каталог: 16.05.2011

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID
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Предметный указатель
Clustering by data type      129—130
Clustering distribution, optimality      315
Clustering in high dimensions      157
Clustering, agglomerative hierarchical algorithms      129
Clustering, algorithm      302
Clustering, arbitrary objects      128
Clustering, array sorting      125
Clustering, average distance      137
Clustering, average-link algorithm      137
Clustering, BIRCH algorithm      131
Clustering, book example      122
Clustering, categorical data      130
Clustering, categorization      128
Clustering, centroid      142
Clustering, computational complexity      157
Clustering, conceptual modeling      129
Clustering, constrained algorithms      130
Clustering, curse of dimensionality      159
Clustering, data normalization      127
Clustering, data squashing      158
Clustering, DBSCAN      151
Clustering, dendrograms      132
Clustering, density-based algorithms      151
Clustering, divisive hierarchical algorithms      129
Clustering, epsilon neighborhood      154
Clustering, Euclidian distance      127
Clustering, fine tuning      316
Clustering, goodness measure      150
Clustering, hierarchical      316
Clustering, hierarchical algorithms      129
Clustering, high dimensionality      158
Clustering, human expert      127
Clustering, iterative optimization      129
Clustering, k-means algorithm      129 142
Clustering, lack of normalization      134
Clustering, large databases      131
Clustering, link-based algorithms      134
Clustering, many dimensions      128
Clustering, mean value      142
Clustering, MST      139
Clustering, news articles      129
Clustering, objective      150
Clustering, overview      128
Clustering, partitional algorithms      129
Clustering, performance, characteristics      157
Clustering, point density      151
Clustering, proximity threshold      135
Clustering, R-trees      158
Clustering, ROCK      147
Clustering, single-link algorithm      135
Clustering, singletons      140
Clustering, Sourceforge-like case study      123
Clustering, spectral methods      130
Clustering, SQL limitations      125
Clustering, SQLEM algorithm      125
Clustering, threshold parameter      129
Clustering, very large datasets      157
Clustering, visual identification      124
Clustering, VLDB      131
Clustering, wavelet methods      130
Clustering, with SQL      124
Cochran’s Q test      233 250 255—256
Codehaus XFire      see “Apache CXF”
Collaboration, as opposed to intelligence      4
Collaborative filtering      see “CF”
Collaborative platforms      5
Collective intelligence      4
Collective knowledge, capture      4
Combination of classifiers      232
Combination of classifiers, computational robustness      233
Combination of classifiers, representational advantage      233
Combination of classifiers, risk reduction      233
Combining classifiers, bagging      234
Combining classifiers, boosting      234
Comparator      126
Complexity, multiclass clasifkation      224
Computational cluster      63
Computational complexity      157
Computational cost      316
Computational linguistics      327
Computational nodes      63
Concept      175 182
ConceptMajorityVoter      264
conceptPriors      50
conceptPriors, map      183
CONCEPT_LABEL_FRAUD      211
CONCEPT_LABEL_VALID      211
conditional probabilities      50 183
Conditional probabilities, user clicks      48
Confidence interval      221
conflict resolution      196—198
Confusion matrix      220 243 259 274
Constrained clustering algorithms      130
Content      13
Content aggregation, digg.com      99
Content aggregator      6 9
Content annotation      9
Content cleansing      283
Content field      27 31
Content impurities      283
Content reconciliation      7
Content similarity, case study      93
Content similarity, normalization      103
Content similarity, text analysis sensitivity      96
Content-based, accumulation and analysis      80
Content-based, recommendation      70
Corcho, Oscar      165
Correlation, complete negative      111
Correlation, complete positive      111
Cosine similarity      95 324
CosineDistance      152
CosineSimilarity      149 187
CosineSimilarityMeasure      95
Cost, function      223 230
Cost, matrix      230
craigslist      13
Crawler      13
Crawler, collecting data      22
Crawler, custom      281
Crawler, fetched documents      24
Crawler, known URLs      24
Crawler, page links      24
Crawler, processed documents      24
Crawling      23 30 281—282
Crawling, Apache Tika      321
Crawling, custom web crawler      320
Crawling, depth of      13
Crawling, Heritrix      321
Crawling, Nutch      321
Crawling, retrieved content structure      282
Crawling, stages of      320
CrawlResultsNewsDataset      284
createClusters      300—301
createClustersWithinTopics      300 305
Credibility of classification      219
Credit card activity      236
Credit risk      233
Credit score      236
Credit worthiness, attributes      235
Credit worthiness, case study      233
Credit worthiness, overview      234
CreditErrorEstimator      244 266 274
Criminal record      236
Cross product calculation      111
Cross-referencing      304
Curse of dimensionality      159 166
CustomAnalyzer      95
Cutting, Doug      22
Dag      172 202
Damping factor      36
DangerousUserType      239
Dangling node      62
Dangling node, heuristic      67
Data diversity      265
Data incongruent      17
Data missing values      17
Data noisy      259
Data normalization      17 156 204
Data normalization, PearsonCorrelation      113
Data preprocessing      204
Data reliability      17
Data renormalization      115
Data representation, inaccuracies      17
Data size issues      18
Data squashing      158
Data understanding      207
Data understanding, importance      279
Data variability      17
DataGenerator      240
Datapoint      146 154
Dataset, dimensionality      156
DataSetAdapter      311
DBSCAN      151
DBSCAN, algorithm      162
DBSCAN, border point      154
DBSCAN, core point      154
DBSCAN, directly density reachable      154
DBSCAN, eps variable      154
DBSCAN, ink drops analogy      151
DBSCAN, minPoints variable      154
DBSCANAlgorithm      152—154
Decision tree      170 245 258 273
Decision tree classification, instability      247
Decision tree classification, interpretation      247
Decision tree, accuracy      246
Decision tree, algorithms      171
Decision tree, classifier      234 266—267
decisionTree, printTree      247
Declarative programming      188
Default analyzer      31
Degree of belief      81
Degree of credibility      223
Degree of freedom      251 255—256
DELPHI      310—311
Delphi, Dataset interface      81
Delphi, inner workings      86
Delphi, recommend      87
Delphi, recommendation engine      80—81
Delphi, similarity between users      82
DelphiUC      103
DelphiUR      103
Dendrogram      132
Dendrogram, data structure      132—133
Dendrogram, initialized      138
Dendrogram, two linked hash maps      132
Dendrogram, visual representation of      132
Density-based, algorithms      151
Density-based, spatial clustering of applications with noise      see “DBSCAN”
dez      165
Dhillon, Inderjit S.      145
Diagnosis of diseases      166
Diagnosis of injuries      166
Diff2PropTest      253
Difference of proportions test      233 250 253
Digg stories, blood donors      146
Digg stories, CSV file      146
Digg stories, Facebook      146
Digg, API      99 146
Digg, RESTful services      14
DiggCategory      100
DiggDelphi, findSimilarUsers      103
DiggDelphi, getTopNFriends      103
DiggDelphi, inner workings      102
DiggDelphi, recommend      103—104
Dimensionality, curse of      157
Directed acyclic graphs      see “DAG”
Directed graph      34
Discourse      288 328
Distance      154
Distance, city block      324
Distance, Euclidean      324
Distance, L2      324
Distance, properties      73
Distance, symmetry      74
Distance, taxi cab      324
Distance, triangle inequality      74
Distributed computing, fallacies      17—19
Distribution of clusters      305
Divisive hierarchical algorithms      129
Docid field      27
DocRank      55—56 280 286
DocRank, inner workings      57
DocRank, matrix builder      57
DocRank, relational tables      61
DocRank, values reused      61
Doctype field      27
Document collection, business news      23
Document collection, Lance Armstrong      23
Document collection, U.S. politics      23
Document collection, world news      23
Document, distance      92
Document, heuristic importance      59
Document, terms      286 288
Domain of discourse      5
Dot (inner) product      96
Drools      165 170 189 193
Drools attribute, no-loop      197
Drools attribute, ruleflow-group      197
Drools attribute, salience      197
Drools, ReteOO      190
DTCreditClassifier      246 259 266
Dunham, Margaret      158
Eclipse      189
Eisner, Jason      161
Elements of intelligence, synergy      100
EM algorithm, E-step      161
EM algorithm, M-step      161
Email categorization      174 178 187
Email classification, blacklists      175
Email classification, header tests      175
Email classification, idiosyncracies      175
Email classification, real-time blackhole lists      175
Email classification, whitelists      175
Email concept, NOT SPAM      178
Email concept, SPAM      178
Email content, congressional elections      175
Email content, global warming      175
Email content, Lance Armstrong      175
Email content, marathon      175
Email content, newspaper advertisement      175
Email content, Nicaragua elections      175
Email content, NVidia stock      175
Email content, Ortega      175
Email content, spam      175
Email content, U.S. politics      175
Email content, world news      175
Email messages, sorting      174
EmailClassifier      175—176 178 184
EmailData      176
EmailDataset      176
EmailDataset, getTrainingSet      178
EmailDataset, setBinary (false)      187
Emaillnstance      178
EmailRuleClassifier      192
Embedding intelligence      11
Engage      9
Ensembles of classifiers      263
Ensembles, accuracy      260
Epictetus      232
Epsilon neighborhood      154
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