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