Data Mining Concepts and Techniques phần 9 pot

... multimedia data mining focuses on image data mining. Mining text data and mining the World Wide Web are studied in the two subsequent638 Chapter 10 Mining Object, Spatial, Multimedia, Text, and Web Data where ... closely linked to imageanalysis and scientiﬁc data mining, and thus many image analysis techniques and scien-tiﬁc data analysis methods can be applied to image data mining. The popular use of the ... data, and computertomography. It is important to explore datamining inraster or image databases.Methodsfor mining raster and image data are examined in the following section regarding themining...

Data Mining Concepts and Techniques phần 1 potx

... Statistical Data Mining 66611.3.3 Visual and Audio Data Mining 66711.3.4 Data Mining and Collaborative Filtering 67011.4 Social Impacts of Data Mining 67511.4.1 Ubiquitous and Invisible Data Mining ... Experiments, and Troubleshooting Techniques Dennis Shasha and Philippe BonnetSQL: 199 9—Understanding Relational Language ComponentsJim Melton and Alan R. SimonInformation Visualization in Data Mining and ... 464Chapter 8 Mining Stream, Time-Series, and Sequence Data 4678.1 Mining Data Streams 4688.1.1 Methodologies for Stream Data Processing and Stream Data Systems 4 69 8.1.2 Stream OLAP and Stream Data...

Data Mining Concepts and Techniques phần 4 potx

... 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-Oriented Induction—An Alternative ... statistical descriptive data mining methods include Cleveland [Cle93] and Devore [Dev95]. Generalization-based induction techniques, such as learning from examples, were proposed and studied in the...

Data Mining Concepts and Techniques phần 8 potx

... 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 ... cite542 Chapter 9 Graph Mining, Social Network Analysis, and Multirelational Data Mining Example 9. 2Backward extension and forward extension. If we want to extend the graph inFigure 9. 7(b), the ... of sequence data include cus-tomer shopping sequences, Web clickstreams, and biological sequences.548 Chapter 9 Graph Mining, Social Network Analysis, and Multirelational Data Mining graph....

Data Mining Concepts and Techniques phần 10 pot

... 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 ... datausingsummaries. 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. Gehrke, and R. Rastogi. Querying and mining ... InProc. 199 9ACM-SIGMOD Int. Conf. Management of Data (SIGMOD 99 ), pages 3 59 370,Philadelphia, PA, June 199 9.[Bre96] L. Breiman. Bagging predictors. Machine Learning, 24:123–140, 199 6.[BRR98] H....

Data Mining Concepts and Techniques phần 2 ppsx

... the2.7 Summary 97 2.7Summary 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 preprocessingincludes ... approximation of the original data. PCA is computationally inexpensive, can be applied to ordered and unorderedattributes, and can handle sparse data and skewed data. Multidimensional data of more than ... (inclusive).2.3 Data Cleaning 652.3.3 Data Cleaning as a ProcessMissing values, noise, and inconsistencies contribute to inaccurate data. So far, we havelooked at techniques for handling missing data and...

Data Mining Concepts and Techniques phần 3 docx

... 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 Technology: An Overview3.3.3 Data ... Jagadish, and Levy [SDJL96]. Methods for cube size esti-mation can be found in Deshpande, Naughton, Ramasamy, et al. [DNR+ 97 ], Ross and Srivastava [RS97], and Beyer and Ramakrishnan [BR 99] . Agrawal,...

Data Mining Concepts and Techniques phần 5 ppt

... to as training tuples and are selected from the database under analysis. In thecontext of classiﬁcation, data tuples can be referred to as samples, examples, instances, data points, or objects.2Because ... Decision Tree Induction 3 09 Figure 6.10 The use of data structures to hold aggregate information regarding the training data (such asthese AVC-sets describing the data of Table 6.1) are one ... scalability.While both SLIQandSPRINThandle disk-resident data sets thatare too large to ﬁt intomemory, the scalabilityof SLIQ islimited by the useof its memory-residentdatastructure.SPRINT removes...

Data Mining Concepts and Techniques phần 6 ppt

... 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 and Norvig [RN95] and Jensen [Jen96]. ... Hecht-Nielsen [HN90], Hertz, Krogh, and Palmer [HKP91], Bishop [Bis95],Ripley [Rip96], and Haykin [Hay 99] . Many books on machine learning, such as [Mit97,RN95], also contain good explanations...

Data Mining Concepts and Techniques phần 7 ppsx

... 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 Shim [GRS99b], and Ganti, Gehrke, and Ramakrishnan ... asCURE by Guha, Rastogi, and Shim [GRS98], ROCK (for clustering categorical attributes)by Guha, Rastogi, and Shim [GRS99b], and Chameleon by Karypis, Han, and Kumar[KHK 99] .For density-based clustering...

Xem thêm