data mining and knowledge management ppt

Data Mining and Knowledge Discovery Handbook, 2 Edition part 2 pptx

... Multimedia Data Mining 58 Data Mining in MedicineNada Lavraˇc, Blaˇz Zupan 111159 Learning Information Patterns in Biological Databases - Stochastic Data Mining Gautam B. Singh 113760 Data Mining ... Determining What Is InterestingSigal Sahar 60331 Quality Assessment Approaches in Data Mining Maria Halkidi, Michalis Vazirgiannis 61332 Data Mining Model ComparisonPaolo Giudici 64133 Data Mining ... Contents XIII54 Collaborative Data Mining Steve Moyle 102955 Organizational Data Mining Hamid R. Nemati, Christopher D. Barko 104156 Mining Time Series Data Chotirat Ann Ratanamahatana,...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 3 pptx

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... understanding phenomena from the data, analysis and prediction.The accessibility and abundance of data today makes Knowledge Discovery and Data Mining a matter of considerable importance and necessity. ... goals, and also on the previous steps.There are two major goals in Data Mining: prediction and description. Predictionis often referred to as supervised Data Mining, while descriptive Data Mining includes ... now avail-able to the researchers and practitioners. No one method is superior to others for allcases. The handbook of Data Mining and Knowledge Discovery from Data aims toorganize all signiﬁcant...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 5 pptx

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... analyze, and investigate such very large data sets hasgiven rise to the ﬁelds of Data Mining (DM) and data warehousing (DW). Withoutclean and correct data the usefulness of Data Mining and data ... examiningdatabases, detecting missing and incorrect data, and correcting errors. Other recentwork relating to data cleansing includes (Bochicchio and Longo, 2003, Li and Fang,1989). Data Mining ... areasthat include data cleansing as part of their deﬁning processes are: data warehousing, knowledge discovery in databases, and data/ information quality management (e.g.,Total Data Quality Management...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 6 ppt

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... Data Warehousing and Knowledge Discovery; 2002 September 04-06; 170-180.Hernandez, M. & Stolfo, S. Real-world Data is Dirty: Data Cleansing and The Merge/PurgeProblem, Data Mining and Knowledge ... Methods, Data Mining and Knowledge Discov-ery Handbook, Springer, pp. 321-352.Simoudis, E., Livezey, B., & Kerber, R., Using Recon for Data Cleaning. In Advances in Knowledge Discovery and Data ... M., Piatetsky-Shapiro, G., & Smyth, P., From Data Mining to Knowledge Dis-covery: An Overview. In Advances in Knowledge Discovery and Data Mining, Fayyad,U. M., Piatetsky-Shapiro, G., Smyth,...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 10 ppt

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... (Silva and Tenenbaum, 2002). Landmark Isomap simply employs land-mark MDS (Silva and Tenenbaum, 2002) to addresses this problem, computing alldistances as geodesic distances to the landmarks. ... clustering and Laplacian eigen-maps are local (for example, LLE attempts to preserve local translations, rotations and scalings of the data) . Landmark Isomap is still global in this sense, but the land-mark ... called Landmark MDS (LMDS) (Silva and Tenenbaum,2002). In LMDS the idea is to choose q points, called ’landmarks’, where q > r(where r is the rank of the distance matrix), but q  m, and to...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 20 ppt

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... for Data Mining, Proc. 22nd Int. Conf. Very Large Databases, T. M. Vijayaraman and AlejandroP. Buchmann and C. Mohan and Nandlal L. Sarda (eds), 544-555, Morgan Kaufmann,1996.Sklansky, J. and ... 2005b, pp 131–158.Rokach, L. and Maimon, O., Clustering methods, Data Mining and Knowledge DiscoveryHandbook, pp. 321–352, 2005, Springer.Rokach, L. and Maimon, O., Data mining for improving the ... TreeConstruction of Large Datasets ,Data Mining and Knowledge Discovery, 4, 2/3) 127-162,2000.Gelfand S. B., Ravishankar C. S., and Delp E. J., An iterative growing and pruning algo-rithm for...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 24 ppt

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... almost as many deﬁnitions of Data Mining as there are treatises on the sub-ject (Sutton and Barto, 1999, Cristianini and Shawe-Taylor, 2000, Witten and Frank,2000,Hand et al., 2001,Hastie et ... 2001b,Dasu and Johnson, 2003), and associated with Data Mining are a variety of names: statistical learning, machinelearning, reinforcement learning, algorithmic modeling and others. By Data Min-ing” ... increases, the space that needs to be ﬁlledwith data goes up as a power function. So, the demand for data increases rapidly, and the risk is that the data will be far too sparse to get a meaningful...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 25 pptx

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... keydistinction between the more effective and the less effective Data Mining proceduresis how overfitting is handled. Finding new and improved ways to fit data is oftenquite easy. Finding ways to ... been included: boost-ing (Freund and Schapire, 1995) and support vector machines (Vapnik, 1995) aretwo obvious candidates. Moreover, the development of new data mining methodsis progressing very ... partition.The data are first segmented left from right and then for the two resulting par-titions, the data are further segmented separately into an upper and lower part. Theupper left partition and the...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 38 pptx

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... type of data is often referred to as relational data. This is as opposed to attribute vector data used by many other unsupervised and supervised Data Mining techniques. In most standard Data Mining ... (eds.), Data Mining and Knowledge Discovery Handbook, 2nd ed., DOI 10.1007/978-0-387-09823-4_18, â Springer Science+Business Media, LLC 2010 17 Constraint-based Data Mining 353F. Bonchi and C. ... Mining. In Proc. ACM SAC’03 - Data Mining Track, pages 437–444, 2003.R. Meo, G. Psaila, and S. Ceri. An extension to SQL for mining association rules. Data Mining and Knowledge Discovery, 2(2):195–224,...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 61 pptx

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... Bradley, U. Fayyad, and C. Reina. Scaling Clustering Algorithms to Large Databases(Extended Abstract). In Proceedings of the ACM SIGMOD Workshop on Research Issuesin Data Mining and Knowledge Discovery, ... show experimental results of running time and cluster quality using arange of data sets of increasing sizes and a high-dimensional data set.First, we use data sets whose distribution follows the ... Proceedings of the SixthACM-SIGKDD International Conference on Knowledge Discovery and Data Mining, Boston, MA, 2000.C. Faloutsos and V. Gaede. Analysis of the Z-ordering Method Using the hausdorff...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 65 ppt

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... left hand side and right hand side of this rule and thus itcan be considered as a representative rule of our data set. Moreover! confidence expresses ourconfidence based on the available data ... in Data Mining 62131.3.1 Association Rules Interestingness MeasuresLet LHS → RHS be an association rule. Further we refer to the left hand side and the righthand side of the rule as LHS and ... left- and right-hand sides correspond to a single attribute.ã Smyth and Goodman’s J-Measure. The J-measure (Smyth and Goodman, 1991) is a mea-sure for probabilistic classification rules and is...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 70 ppt

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... an evaluation data set.A different line of attacking the multi-label feature selection problem is to transform themulti-label data set into one or more single-label data sets and use existing ... for single-label data, such as linear discriminantanalysis (LDA), require modification prior to their application to multi-label data. LDA hasbeen modified to handle multi-label data in (Park & ... for textual data, such asthe MeSH1for medical articles and the ACM computing classification system2for computer1www.nlm.nih.gov/mesh/2www.acm.org/class/ 34 Mining Multi-label Data 677Label...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 74 pptx

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... K., Kargupta, H., Ryan, J. (2006) Random projection based multiplicative data pertur-bation for privacy preserving data mining, IEEE Trans. on Knowledge and Data Engi-neering 18:1 92-106.Machanavajjhala, ... protection of continuous microdata, Data Mining and Knowledge Discovery, 11:2 181-193.Moore, R. (1996) Controlled data swapping techniques for masking public use microdatasets, U. S. Bureau of ... L. Rokach (eds.), Data Mining and Knowledge Discovery Handbook, 2nd ed., DOI 10.1007/978-0-387-09823-4_36, â Springer Science+Business Media, LLC 2010 35 Privacy in Data Mining 7110 204060801000...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 76 pptx

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... Metrics for Evaluation of Data- mining Algorithms. In Proceedings of the Third International Conference on Knowledge Discovery and Data- Mining, 1997.Paterson, I. New Models for Data Envelopment Analysis, ... b and minimizing squared error onthe learning set, we obtain the estimations given in the left part of Figure 39.1 for twoO. Maimon, L. Rokach (eds.), Data Mining and Knowledge Discovery Handbook, ... Integration and Collaboration Aspects of Data Mining, Decision Support and Meta-Learning, 111-122. University of Helsinki,2002.Pfahringer, B., Bensusan, H., Giraud-Carrier, C. Meta-learning by Landmarking...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 78 ppt

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... statistics, ma-chine learning, and data visualization. Data mining has emerged as a direct outcomeof the data explosion that resulted from the success in database and data warehous-ing technologies ... during Data Mining to help identify rare cases.For example, in association rule mining a human expert may indicate which prelim-inary results are interesting and warrant further mining and which ... of rare cases. These metrics can then bet-ter guide the Data Mining process and better evaluate the results of Data Mining. Precision and recall are metrics from the information retrieval community...