DATA MINING AND MANAGEMENT -- DATA MINING AND MANAGEMENT -- CONTENTS -- PREFACE -- Chapter 1COGNITIVE FINANCE: DATA ANALYSIS WITH ABEHAVIORAL EDGE -- Abstract -- Introduction -- Context Specific Strategy Usage -- Changes in Strategies -- Behavioral Finance -- Methods for Capturing Cognitive Processes -- Spending Strategies -- Behavioral Evaluation -- Use of Behavioral Data -- Saving Strategies -- Saving Concept Study -- Saving Differences Study -- Saving Solutions -- Conclusion -- Characterizing Mental Processes -- Financial Personality -- Cognitive Approaches to Finance -- References -- Chapter 2THE DATA MINING PERSPECTIVE OF THE INDIANMINERAL INDUSTRY -- Abstract -- 1.0. Introduction -- 1.1. Preamble -- Aim And Scope of this Chapter -- 1.2. An Overview of Mineral Production in India -- 1.4. Key Issues of the Mineral Industry -- 1.4. Impacts of Mineral Industries -- 1.5. Necessity of EIA Studies -- 2.0. Impacts of Coal Mining Projects -- 2.1. Impacts of Coal Mining on Air -- 2.2. Impacts of Coal Mining on Water -- 2.3. Impacts of Coal Mining on Land -- 2.4. Impact of Coal Mining on Noise -- 2.5. Impacts of Mining on Socioeconomic Aspects -- 2.6. EIA Studies for Coal Mining Projects -- 3.0. Impacts of Coal Washery Projects -- 3.1. Impacts of Coal Washery Projects on Air Environment -- 3.2. Impacts of Coal Washery Projects on Water Environment -- 3.3. Impacts of Coal Washery Projects on Socioeconomic Environment -- 3.4. EIA Studies for Coal Washery Projects -- 4.0. Impacts of Coke Plants -- 4.1. Impacts of Coke Plants on Air Environment -- 4.2. Impacts of Coke Plant on Water Environment -- 5.0. Impacts due to the Power Sector -- 6.0. Impacts of Iron Ore Benificiation Plants -- 7.0. Impacts of Copper Ore Benificiation Plants -- 8.0. Impacts of Small-Scale Mines -- 9.0. Data Mining of the Mineral Industry.

9.1. Assessment of Impacts due to Coal Mining -- 9.1.1. Assessment of Impacts on Air Environment -- 9.1.2. Assessment of Impacts on Water Environment -- 9.1.3. Assessment of Impacts on Land Environment -- 9.1.4. Impact of Coal Mining on Noise Environment -- 9.1.5. Impacts on Socioeconomic Environment -- 9.1.6. EIA Studies for Coal Mining Projects -- 9.2. Assessment of Impacts due to Coal Washery Projects -- 9.2.1. Impacts of Coal Washery Projects on Air Environment -- 9.2.2. Assessment of Impacts of Coal Washery Projects on Water -- 9.2.3. Impacts of Coal Washery Projects on Socioeconomic Environment -- 9.2.4. EIA Studies for Coal Washery Projects -- 9.3. Assessment of Impacts due to Coke Plants -- 9.3.1. Impacts of Coke Plants on Air Environment -- 9.3.2. Impacts of Coke Plant on Water Environment -- 9.4. Assessment of Impacts due to Power Sector -- 9.5. Assessment of Impacts due to Iron Ore Beneficiation Plants -- 9.6. Assessment of Impacts due Copper Ore Beneficiation Plants -- 9.7. Assessment of Impacts due to Small-Scale Mines -- 10.0. Management Strategies -- 10.1. Pre-Mining Investigations -- 10.2. Pollution Prevention and Controls -- 10.3. Mine Closure -- 10.4. Environmental Laws in the Indian Context -- 10.5. Contributions from Resident Universities -- 11.0. Conclusion -- 12.0. Scope of Further Research -- References -- Chapter 3ADDING TIME DIMENSION TO XML -- Abstract -- Expert Commentary to Chapter Adding Time Dimension to XML -- 1. Introduction -- 1.1. Problem Statement -- 1.2. Organization of the Chapter -- 2. State of Art -- 3. 3D_XML: A Three-Dimensional XML-Based Model -- 3.1. Time Dimensions -- 3.2. Time Model -- 3.3. Data Modeling -- 3.4. Storage of Temporal XML Documents -- A Comparison between XML-Enabled Databases and NXDs -- An Open Source NXD (eXist) -- 3.5. Temporal Constructs -- Supporting For "Now" -- Get Time Dimensions.

3.6. Manipulation System of 3D_XML Model -- 3.6.1. Update in eXist: A Brief Overview -- Insert -- Replace -- Delete -- Rename -- Value -- 3.6.2. Data Manipulation System of 3D_XML -- Insert -- Insert a New Element -- Insert a New Attribute -- Delete -- Update -- 3.6.3 Time Dimensions Manipulation System of 3D_XML -- Restrict Valid Time -- Extend Valid Time -- Checksibling_Versions -- Covering_Constraint -- Delete_Element -- Construct_Element -- Temporal Constructs to Manipulate Time Dimensions -- Delete_Validtime -- Extend_Validtime -- 3.6.4. Temporal Constructs to Manipulate Data/Time Dimensions -- Temporal Constructs To Manipulate Data -- 4. A Guide to eXist -- 4.1. Introduction -- 4.2. Installing eXist -- Software Required Befor Installation -- 4.3. Start Working with eXist -- Using the Java Admin Client -- Loading Data into eXist -- Executing Query in eXist -- Accessing the Server -- Shutting Down the Database -- 5. Conclusion -- Acknowledgments -- References -- Chapter 4STATISTICAL LEARNING METHODS FOR COMBININGTECHNICAL TRADING RULES AND PREDICTINGTHE STOCK MARKETS -- Abstract -- 1. Introduction -- 2. Technical Trading Rules -- 3. Ensemble Learning Methods -- 3.1. The Boosting Method -- 3.2. The Bayesian Model Averaging Approach and Committee -- 3.3. The Classical Combining Preductions Procedure -- 4. Fitness Measures and Signals Filtering -- 5. Empirical Results -- 6. Conclusions -- Acknowledgment -- References -- Chapter 5MODEL SELECTION USING DATA MINING -- Abstract -- 1. Introduction -- 2. The Problem Concerning the Building of a Multiple RegressionModel -- 3. The GASIC Approach for Selecting Regressors via GeneticAlgorithms -- 4. Comparing GASIC with Previous Procedures for SelectingModels -- 5. A Specific Example: Using GASIC in the Selection of Shares forTracking the IBEX35 Spanish Stock Market Index -- 6. Conclusion -- References.

Chapter 6MANAGING BUILDING INFORMATION MODELS -- 1. Introduction -- 2. History of Building Information Models -- 2.1. Early Efforts -- 2.2. STEP Based Semantic Models for Buildings -- 3. Defining Building Information Models -- 4. Managing Building Information Models -- 4.1. The Current Schema Standard: Industry Foundation Classes (IFC) -- A. Resource Layer -- B. Core Layer -- C. Interoperability Layer -- D. Domain Layer -- 4.2. Managing Building Information Models: The IFC Perspective -- 4.3. Shared Database Approach -- 4.4. Model Management at the Back-End -- 4.5. BIM Based Web Services -- 5. Summary -- References -- Chapter 7MODELING THE AUDITORS' OPINIONS BY USINGASSOCIATION RULES -- Abstract -- I. Introduction -- II. Former Research -- III. Research Methodology -- Sample Construction -- Variables -- Methods -- IV. Experiments and Results Analysis -- V. Conclusion -- References -- Chapter 8SPATIO-TEMPORAL DATA MANAGEMENTFOR ENVIRONMENTAL MODELING OF DUSTDISPERSION OVER OPENCAST COAL MINING AREAS -- Abstract -- 1. Introduction -- 2. Spatio-Temporal Data Management -- 3. Spatio-Temporal Data Sources -- 3.1. Terrain Observations -- 3.2. Remote Sensing -- 3.3. GPS Mapping -- 3.4. Monitoring Systems and Spatio-Temporal Modeling -- 4. A Case Study: A Spatio-Temporal Data Model forEnvironmental Modeling of Dust Dispersionover Opencast Coal Mining Areas -- 5. Discussion -- 6. Conclusion -- Acknowledgment -- References -- Chapter 9CHALLENGES AND FUTURE TRENDS IN QUERYINGSEMANTIC WEB DATA STREAMS -- Abstract -- 1. Introduction -- 2. RDF -- 3. Ontology -- 4. SPARQL -- 5. Querying Semantic Web Data Streams -- 2.1. Logical Optimization -- 2.2. Physical Optimization -- 3. Considering Ontology Data -- 3.1. Optimizing Test of Conformance and Inference -- 4. Summary and Conclusions -- 8. Biography -- References -- Chapter10ANEWCO-TRAININGMETHODFORDATAMINING.

Abstract -- 1.Introduction -- 2.RelatedWork -- 2.1.Co-TrainingMethod -- 2.2.IncrementalandIterativeLearningMethods -- 3.DescriptionoftheProposedMethod -- 3.1.LimitationsoftheCurrentMethod -- 3.2.ANewCo-TrainingMethod -- 4.ExperimentalResults -- 5.Conclusions -- Acknowledgment -- References -- Chapter11HESTIA:∗HISTORICALLY-ENABLEDSPATIO-TEMPORALINFORMATIONANONYMITY -- Abstract -- 1.Introduction -- 2.Terminology -- 3.TheHESTIAFramework -- 3.1.Component-BasedDescriptionoftheHESTIASystem -- 3.2.AScenariooftheHESTIASystemOperation -- 4.TheFree-TerrainModel -- 4.1.PhaseI:ReconstructionofUserMovementHistory -- 4.2.PhaseII:DerivationoftheUnsafeRoutes -- 4.3.PhaseIII:TrajectoryK-anonymity -- 4.3.1.MatchingofaUserRequesttoanUnsafeRoute -- 4.3.2.OfferingofTrajectoryK-Anonymity -- 4.4.PhaseIV:ServiceDelayorDenial -- 4.5.AchievingReal-timeOperation -- 4.6.SystemImplementationDetails -- 5.ExperimentalEvaluation -- 6.RelatedWork -- 7.Conclusion -- Acknowledgment -- References -- Chapter12BINOMIALP-SPLINEREGRESSIONFORANOMALYDETECTIONINCOHORTMORTALITYPATTERNS -- Abstract -- 1.Introduction -- 2.OccurrenceDatawithChangePoints -- 2.1.BinomialP-splineModel -- 2.2.SmoothingParameterSelection -- 2.3.TheWaldShaverMethod -- 3.SimulationStudies -- 3.1.ModelFitting -- 3.2.ModelSelection -- 4.ApplicationtoCancerMortalityDetection -- 5.Conclusion -- Acknowledgment -- A.AuxiliaryResultsandProofs -- References -- INDEX.