1 . Data Architecture
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2 . Introduction To Data Mining
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3 . Data-warehouses
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4 . Relational Databases
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5 . Classification Of Data Mining Systems
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6 . Data Mining Functionalities
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7 . Clustering And Sampling
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8 . Transactional Databases
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9 . Data Cleaning
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10 . Dimensionality Reduction
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11 . Major Issues In Data Mining
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12 . Data Reduction
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13 . Advanced Data And Information Systems And Advanced Applications
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14 . Data Cleaning Process
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15 . Noisy Data
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16 . Data Transformation
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17 . Descriptive Data Summarization
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18 . Data Mining Task Primitives
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19 . Introduction To Data Preprocess
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20 . Performance Issues In Data Mining
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21 . Data Integration And Transformation
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22 . Numerosity Reduction
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23 . Graphic Displays Of Basic Descriptive Data Summaries
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24 . Measuring The Dispersion Of Data
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25 . Data Discretization And Concept Hierarchy Generation
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26 . Concept Hierarchy Generation For Categorical Data
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27 . Integration Of A Data Mining System With A Datawarehouse System
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28 . Star-cubing: Computing Iceberg Cubes Using A Dynamic Star-tree Structure
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29 . Multiway Array Aggregation For Full Cube Computation
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30 . Differences Between Operational Database Systems And Data Warehouses
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31 . Pre-computing Shell Fragments For Fast High-dimensional Olap
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32 . Introduction To Data Warehouses
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33 . Data Warehouse Architecture
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34 . A Multidimensional Data Model
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35 . Data Warehouse Implementation
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36 . On-line Analytical Processing To On-line Analytical Mining
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37 . The Process Of Data Warehouse Design
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38 . Data Warehousing To Data Mining
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39 . A Three-tier Data Warehouse Architecture
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40 . Attribute-oriented Induction For Data Characterization
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41 . Data Warehouse Back-end Tools And Utilities
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42 . Methods For Data Cube Computation
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43 . Attribute-oriented Induction
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44 . Types Of Olap Servers: Rolap Versus Molap Versus Holap
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45 . Mining Class Comparisons: Discriminating Between Different Classes
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46 . Efficient Implementation Of Attribute-oriented Induction
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47 . Complex Aggregation At Multiple Granularity: Multi Feature Cubes
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48 . Driven Exploration Of Data Cubes
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49 . Mining Closed Sequential Patterns
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50 . Prefix Span: Prefix-projected Sequential Pattern Growth
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51 . Frequent Pattern Based Clustering Methods
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52 . Frequent-pattern Mining In Data Streams
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53 . Vector Objects
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54 . Stream: A K-medians-based Stream Clustering Algorithm
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55 . User-constrained Cluster Analysis
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56 . Chameleon: A Hierarchical Clustering Algorithm Using Dynamic Modeling
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57 . Clique: A Dimension-growth Subspace Clustering Method
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58 . Spade: An A Priori-based Vertical Data Format Sequential Pattern Mining Algorithm
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59 . Ratio-scaled Variables
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60 . Sting: Statistical Information Grid
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61 . Rock: A Hierarchical Clustering Algorithm For Categorical Attributes
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62 . Representative Object-based Technique
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63 . Periodicity Analysis For Time-related Sequence Data
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64 . Similarity-search-methods
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65 . Density-based Methods
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66 . Constraint-based Cluster Analysis
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67 . Denclue: Clustering Based On Density Distribution Functions
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68 . Distance-based Outlier Detection
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69 . Stream Olap And Stream Data Cubes
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70 . Model-based Clustering Methods
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71 . Mining Sequence Patterns In Biological Data
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72 . Ordinal Variables
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73 . Scalable Methods For Mining Sequential Patterns
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74 . Grid-based Methods
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75 . Mining Sequence Patterns In Transactional Databases
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76 . Constraint-based Mining Of Sequential Patterns
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77 . Baum-welch Algorithm
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78 . Very Fast Decision Tree (Vfdt) And Concept-adapting Very Fast Decision Tree (Cvfdt)
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79 . Clustering Evolving Data Streams
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80 . Methodologies For Stream Data Processing And Stream Data Systems
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81 . Clustering With Obstacle Objects
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82 . Statistical Distribution-based Outlier Detection
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83 . Categorical Variables
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84 . Outlier Analysis
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85 . Challenges In Clustering
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86 . Clustering High-dimensional Data
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87 . Mining Time-series Data
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88 . Interval-scaled Variables
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89 . Binary Variables
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90 . Viterbi Algorithm
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91 . Types Of Data In Cluster Analysis
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92 . Classical Partitioning Methods: K-means And K-medoids
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93 . Neural Network Approach
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94 . Mining Data Stream
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95 . Semi-supervised Cluster Analysis
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96 . Proclus: A Dimension-reduction Subspace Clustering Method
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97 . Forward Algorithm
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98 . Introduction To Cluster
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99 . Deviation-based Outlier Detection
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100 . A Categorization Of Major Clustering Methods
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101 . Hidden Markov Model For Biological Sequence Analysis
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102 . Conceptual Clustering
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103 . Hierarchical Methods
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104 . Similarity Search In Time-series Analysis
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105 . Classification Of Dynamic Data Streams
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106 . Training Bayesian Belief Networks
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107 . Wave Cluster: Clustering Using Wavelet Transformation
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108 . Estimating Confidence Intervals
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109 . Rule Induction Using A Sequential Covering Algorithm
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110 . The Apriori Algorithm
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111 . Frequent Patterns
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112 . Support Vector Machines
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113 . Roc Curves
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114 . Mining Customer Networks For Viral Marketing
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115 . Genetic Algorithms
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116 . Generalization Of Object Identifiers And Class/subclass Hierarchies
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117 . Decision Tree Induction
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118 . Mining Frequent Itemsets Using Vertical Data Format
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119 . Data Mining System Products And Research Prototypes
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120 . Bagging
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121 . Introduction To Classification And Prediction
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122 . Classification And Prediction Analysis Of Multimedia Data
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123 . Mining Spatial Association And Co-location Patterns
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124 . Naive Bayesian Classification
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125 . Data Mining In Other Scientific Applications
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126 . Mining Multilevel Association Rules
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127 . Multi-relational Classification Using Tuple Id Propagation
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128 . Bayesian Classification
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129 . Graph Indexing With Discriminative Frequent Substructures
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130 . Association Mining To Correlation Analysis
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131 . Bayesian Belief Networks
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132 . Introduction To Data Mining Applications
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133 . Adaboost, A Boosting Algorithm
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134 . Multidimensional Analysis And Descriptive Mining Of Complex Data Objects
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135 . Classification By Decision Tree Induction
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136 . Evaluating The Accuracy Of A Classifier Or Predictor
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137 . Generalization Of Structured Data
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138 . Mining Variant And Constrained Substructure Patterns
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139 . Comparing Classification And Prediction Methods
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140 . Data Mining For The Telecommunication Industry
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141 . Mining Multimedia Data On The Web
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142 . Introduction To Back Propagation
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143 . Document Clustering Analysis
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144 . Efficient And Scalable Frequently Itemset Mining Methods
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145 . Constraint-based Association Mining
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146 . Tree Pruning
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147 . Community Mining From Multi Relational Networks
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148 . Mining Multidimensional Association Rules
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149 . Rule Extraction From A Decision Tree
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150 . Mining Associations In Multimedia Data
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151 . Ubiquitous And Invisible Data Mining
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152 . Rule Pruning
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153 . Data Mining, Privacy, And Data Security
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154 . Mining Quantitative Association Rules
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155 . Tuple Id Propagation
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156 . Preparing The Data For Classification And Prediction
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157 . Spatial Data Cube Construction And Spatial Olap
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158 . Defining A Network Topology
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159 . Dimensionality Reduction For Text
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160 . Associative Classification: Classification By Association Rule Analysis
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161 . Scalability And Decision Tree Induction
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162 . Aggregation And Approximation In Spatial And Multimedia Data Generalization
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163 . Mining The Web's Link Structures To Identify Authoritative Web Pages
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164 . A Multilayer Feed-forward Neural Network
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165 . Using If-then Rules For Classification
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166 . Mining The World Wide Web
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167 . Data Mining And Collaborative Filtering
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168 . Mining The Web Page Layout Structure
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169 . Social Network Analysis
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170 . Introduction To Graph Mining
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171 . Text Mining Approaches
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172 . Classification And Cluster Analysis Using Graph Patterns
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173 . Pattern-growth Approach
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174 . Statistical Data Mining
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175 . Characteristics Of Social Networks
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176 . Text Retrieval Methods
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177 . Trends In Data Mining
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178 . Text Mining
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179 . Data Mining For Intrusion Detection
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180 . General Theory Of Pipeline
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181 . Ilp Approach To Multi-relational Classification
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182 . Methods For Mining Frequent Sub Graphs
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183 . Text Indexing And Query Processing Techniques
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184 . Mining Newsgroups Using Networks
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185 . Link Mining: Tasks And Challenges
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186 . Multi-relational Data Mining
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187 . Text Data Analysis And Information Retrieval
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188 . Link Prediction: What Edges Will Be Added To The Network
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189 . Multimedia Data Mining
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190 . Visual And Audio Data Mining
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191 . Spatial Clustering Methods
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192 . Web Usage Mining
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193 . Multi-relational Clustering With User Guidance
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194 . Audio And Video Data Mining
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195 . Examples Of Commercial Data Mining Systems
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196 . Spatial Data Mining
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197 . Substructure Similarity Search In Graph Databases
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198 . Theoretical Foundations Of Data Mining
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199 . Data Mining For Biological Data Analysis
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