... multimedia data mining focuses on image data mining.
Mining text data and mining the World Wide Web are studied in the two subsequent
638 Chapter 10 Mining Object, Spatial, Multimedia, Text, and Web Data
where ... closely linked to image
analysis and scientific data mining, and thus many image analysis techniques and scien-
tific data analysis methods can be ap...
... Statistical Data Mining 666
11.3.3 Visual and Audio Data Mining 667
11.3.4 Data Mining and Collaborative Filtering 670
11.4 Social Impacts of Data Mining 675
11.4.1 Ubiquitous and Invisible Data Mining ... Experiments, and Troubleshooting Techniques
Dennis Shasha and Philippe Bonnet
SQL: 199 9—Understanding Relational Language Components
Jim Melton and Alan R...
... include data cube–based data aggregation and attribute-
oriented induction.
From a data analysis point of view, data generalization is a form of descriptive data
mining. Descriptive data mining ... [CCH91] and
further extended by Han, Cai, and Cercone [HCC93], Han and Fu [HF96], Carter and
Hamilton [CH98], and Han, Nishio, Kawano, and Wang [HNKW98].
4.3 Attribute-...
... substructures.
9. Metadata mining. Metadata are data about data. Metadata provide semi-structured
data about unstructured data, ranging from text and Web data to multimedia data-
bases. It is useful for data ... cite
542 Chapter 9 Graph Mining, Social Network Analysis, and Multirelational Data Mining
Example 9. 2
Backward extension and forward extension. If we want...
... multidimen-
sional databases. SIGMOD Record, 26:12–17, 199 7.
[BS97b] A.BersonandS.J.Smith.DataWarehousing,DataMining,andOLAP.McGraw-Hill, 199 7.
[BST 99] A. Berson, S. J. Smith, and K. Thearling. Building Data Mining ... datausing
summaries. In Proc. 199 9 Int. Conf. Knowledge Discovery and Data Mining (KDD 99 ),
pages 73–83, San Diego, CA, 199 9.
[GGR02] M. Garofalakis, J. Gehrk...
... the
2.7 Summary 97
2.7
Summary
Data preprocessing is an important issue for both data warehousing and data mining,
as real-world data tend to be incomplete, noisy, and inconsistent. Data preprocessing
includes ... approximation of the original data.
PCA is computationally inexpensive, can be applied to ordered and unordered
attributes, and can handle sparse data and...
... and
Wang [HHW97] and Hellerstein, Avnur, Chou, et al. [HAC
+
99 ]. Techniques for esti-
mating the top N queries are proposed in Carey and Kossman [CK98] and Donjerkovic
and Ramakrishnan [DR 99] . Further ... Kimball and Ross [KR02], Imhoff, Galemmo, and
Geiger [IGG03], Inmon [Inm96], Berson and Smith [BS97b], and Thomsen [Tho97].
134 Chapter 3 Data Warehouse and OLAP...
... to as training tuples and are selected from the database under analysis. In the
context of classification, data tuples can be referred to as samples, examples, instances,
data points, or objects.
2
Because ... Decision Tree Induction 3 09
Figure 6.10 The use of data structures to hold aggregate information regarding the training data (such as
these AVC-sets describing the data of...
... functions
(Hanson and Burr [HB88]), dynamic adjustment of the network topology (Me´zard
and Nadal [MN 89] , Fahlman and Lebiere [FL90], Le Cun, Denker, and Solla [LDS90],
and Harp, Samad, and Guha [HSG90] ), and ... and Herskovits [CH92], Buntine [Bun94], and Heckerman, Geiger, and Chick-
ering [HGC95]. Algorithms for inference on belief networks can be found in Russell
a...
... efficiently.
8
Mining Stream, Time-Series,
and Sequence Data
Our previous chapters introduced the basic concepts and techniques of data mining. The techniques
studied, however, were for simple and structured ... Rumelhart and Zipser [RZ85].
Scalable methods for clustering categorical data were studied by Gibson, Kleinberg,
and Raghavan [GKR98], Guha, Rastogi, and Shi...