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Visual Data Mining and Document Collections Visualization - USP

Visual Data Mining and Document Collections Visualization - USP

Visual Data Mining and Document Collections Visualization -

Universidade de São Paulo, São Carlos/SP, BrasilInstituto de Ciências Matemáticas e de Computação (ICMC)Departamento de Ciências da ComputaçãoIntroduction• Visualization and Data AnalysisVisual Data Mining and DocumentCollections VisualizationFernando Vieira Paulovichpaulovic@icmc.usp.br• InfoVis2– Visualization– Sonification– Mining• Partners– M. Cristina F. Oliveira - Roberto Pinho– Alneu de Andrade Lopes - Lionis Watanabe– Luis Gustavo Nonato - Pedro Vilela– Guilherme P. Telles– Haim Levkowitz2Mining Large Data Sets - MotivationWhat is (not) Data Mining?4.000.0003.500.0003.000.0002.500.0002.000.0001.500.0001.000.000500.0000The Data GapTotal new disk (TB) since 1995Number ofanalysts1995 1996 1997 1998 1999• What is not DataMining?– Look up phonenumber in phonedirectory– Query a Websearch engine forinformation about“Amazon”• What is Data Mining?– Certain names are moreprevalent in certain USlocations (O’Brien, O’Rurke,O’Reilly… in Boston area)– Group together similardocuments returned bysearch engine according totheir context (e.g. Amazonrainforest, Amazon.com)34Origins of Data Mining• Draws ideas from machine learning/AI, patternrecognition, statistics, and database systems• Traditional Techniquesmay be unsuitable due to– Enormity of data– High dimensionalityof data– Heterogeneous,distributed natureof dataStatistics/AIData MiningDatabasesystemsMachine Learning/PatternRecognitionData Mining Tasks• Prediction Methods– Use some variables to predict unknown orfuture values of other variables• Description Methods– Find human-interpretable patterns thatdescribe the dataFrom [Fayyad, et.al.] Advances in Knowledge Discovery and Data Mining, 1996561

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