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TABLEAU 2 DATA MINING PROBLEM TYPES
Table1. Data mining problems and solutions
Table 1 Problem parameters for our data mining application
Table 1: Problem parameters for our data mining application.
Table 4: Industrial HPCC Applications 14 to 18: Information Analysis|\DataMining quot; Application Area Problem Machine
1995
"... In PAGE 7: ...Table4 : Industrial HPCC Applications 1 to 5: SIMULATION Application Area Problem Machine Item and Examples Comments and Software 1 Computational PDE, FEM SIMD, MIMD for Fluid Dynamics Turbulence irregular adaptive Aerospace Mesh Generation HPF(+) but Military, Civilian Unclear for Vehicles adaptive irregular Propulsion mesh 2 Structural PDE, FEM MIMD as complex Dynamics Dominated by geometry Vendor Codes such HPF(+) as NASTRAN 3 Electromagnetic PDE solved by Simulation moment method SIMD Antenna Design Matrix solve HPF Stealth Vehicles dominates Noise in high Newer FEM and SIMD, MIMD frequency circuits FD Methods? HPF(+) Mobile Phones Also fast multipole 4 Scheduling Expert Systems MIMD Manufacturing and/or (unclear Speedup) Transportation AsyncSoft (Dairy delivery to Neural Networks SIMD Military deployment) Simulated annealing HPF University Classes Linear Programming MIMD Airline Scheduling (hard sparse matrix) HPF+? of crews, planes in static or dynamic (Syracuse snow storm) cases 5 Environmental PDE, FD, FEM SIMD but Modeling| Sensitivity to MIMD for Earth/Ocean/Atmos- Data irregular adaptive pheric Simulation mesh HPF(+) except this unclear for adaptive irregular mesh... In PAGE 8: ...Table4 : Industrial HPCC Applications 6 to 10: SIMULATION Application Area Problem Machine Item and Examples Comments and Software 6 Environmental Empirical Models Some SIMD but Phenomenology Monte Carlo and MIMD more |Complex Systems, Histograms natural (Lead Concentration HPF in blood) 7 Basic Chemistry Calculate Matrix Probably SIMD Chemical Potentials Elements with perhaps Elemental Reaction Matrix Eigenvalue SIMD possible Dynamics determination, HPF Inversion, Multiplication 8 Molecular Dynamics Particle Dynamics HPF(+) except in Physics amp; Chemistry with irregular need MPF for Biochemistry cuto forces fast multipole Discrete Simulation Fast Multipole Monte Carlo for Methods CFD (DSMC) Mix of PDE and Particle in the Cell Particle methods (PIC) in PIC and DSMC 9 Economic Modelling Single nancial Real Time instrument by SIMD, HPF Optimization Monte Carlo Mortgaged backed Full Simulations MIMD or SIMD Securities of complete with Integration Option Pricing portfolios Software 10 Network Simulations Sparse matrices MIMD Electrical Circuit Zero structure HPF for matrix Microwave and VLSI de ned by elements Biological (neural) connectivity MPF or library Circuit for matrix solve... In PAGE 9: ...Table4 : Industrial HPCC Applications 11 to 13: SIMULATION Application Area Problem Machine Item and Examples Comments and Software 11 Particle Transport Monte Carlo Methods Problems as in neutron MIMD transport for (nuclear) HPF explosion simulations 12 Graphics (rendering) HPF for simple ray Hollywood Several Operational tracing but MPF Virtual Reality Parallel Ray tracers for best algorithms Distributed model MIMD amp; Asyncsoft hard for distributed database 13 Integrated Complex Event Driven Timewarp or other System Simulations (ED) and Event Driven Defense (SIMNET, Time stepped Simulation needs Flight Simulators) (TS) simulations Appropriate Education Virtual Reality Asyncsoft (SIMCITY) Interfaces Integration Multimedia/VR in Database backends Software Entertainment Interactive Database Multiuser Virtual HPF+ for TS Worlds Simulation Chemical and Nuclear Plants... In PAGE 11: ...Table4 : Industrial HPCC Applications 19 to 22 for Information Access InfoVision|Information, Video, Imagery and Simulation on Demand Application Problem Machine amp; Item Area Comments Structure Software 19 Transaction Database-most Embarrassingly MIMD Processing transactions short. Parallel Database ATM As add \value quot; (automatic this becomes teller machine) Informationintegration 20 Collaboration Research Center or Asynchronous High Speed Telemedicine doctor(s)|patient Network Collaboratory interaction without for Research regard to physical Education location Business 21 Text on Multimedia Embarrassingly MIMD Demand database Parallel Database Digital (existing) (see areas 22, 23) libraries Full text search ERIC Education database, United Nations- Worldwide newspapers 22 Video on Multimedia Embarrassingly MIMD Demand Database Parallel for Database Movies, News Interactive VCR, multiple Users Video Editing (CNN Newsource Video Browsing, Software amp; Newsroom), Link of Interesting Current cable, video and text parallel United Nations- database compression SIMD Policy Support compression... In PAGE 12: ...Table4 : Industrial HPCC Applications 23 to 24 for Information Access InfoVision|Information, Video, Imagery and Simulation on Demand Application Problem Machine amp; Item Area Comments Structure Software 23 Imagery on Multimedia Metaproblem MIMD but Demand database Embarrassingly much SIMD Kodak GIODE Image Parallel plus image \clip art quot; on Understanding for Loosely analysis demand Content searching Synchronous Medical images and (terrain) Image Satellite images medical feature Understanding identi cation 24 Simulation on Multimedia map Synchronous SIMD terrain Demand database terrain engine (parallel Education, Generalized rendering with rendering) Tourism, City ight simulator Asynchronous MIMD planning, Geographical Hypermedia database Defense Information Integration mission planning System software... In PAGE 13: ...Table4 : Information Integration Applications 25 to 28 These involve combinations of Information Production, analysis, Access and Dissemination and thus need the Integration of the various Software and Machines Architecture Issues discussed under previous application areas. Sometimes Called System of Systems 25: Military and Civilian Command and Control (C2, C3, C4I : : :) Battle Management, Command, Control, Communication, Intelligence and Surveillance (BMC3IS) Military Decision Support Crisis Management|Police and other Government Operations SIMNET simulates this and with people and computers in the loop has many of same issues 26 to 28: Applications of InfoVision Services Generalize Compuserve, Prodigy, America Online, Dialog and Other In- formation Services 26: Decision Support for Society Community Information Systems Travel and Generalized Yellow Page Services 27: Business Decision Support|One example is: Health Care with Image and Video databases supporting telemedicine 28: Public Administration and Political Decision Support Government Information Systems Maxwell School at Syracuse University teaches use of realtime video to aid world wide decisions (United Nations)... In PAGE 14: ...Table4 : Information Integration Applications 29 to 33 29: Real-Time Control Systems Robotics uses Imagery to make decisions (control vehicles) Energy management controls power use and generation 30: Electronic Banking Requires Security, Privacy, Electronic Cash, etc. 31: Electronic Shopping 32: Agile Manufacturing|Multidisciplinary Design and Concurrent Engineering Combines CAD with Applications 1 to 3 Requires major changes to Manufacturing Infrastructure and Approach 33: Education InfoMall Living Textbook|6 Schools on ATM network linked to HPCC InfoVision Servers at NPAC [Mills:95a] Table 1 describes the general guidelines used in organizing Table 4.... In PAGE 14: ... 29: Real-Time Control Systems Robotics uses Imagery to make decisions (control vehicles) Energy management controls power use and generation 30: Electronic Banking Requires Security, Privacy, Electronic Cash, etc. 31: Electronic Shopping 32: Agile Manufacturing|Multidisciplinary Design and Concurrent Engineering Combines CAD with Applications 1 to 3 Requires major changes to Manufacturing Infrastructure and Approach 33: Education InfoMall Living Textbook|6 Schools on ATM network linked to HPCC InfoVision Servers at NPAC [Mills:95a] Table 1 describes the general guidelines used in organizing Table4 . Note that we did not directly cover academic areas, and a more complete list (which included our industrial table) was produced by the Peta ops meeting [Peta:94a].... In PAGE 14: ... Here, \Info quot; refers to the information based application focus and \Mall quot; to the use of a virtual corporation (groups of \storeholders quot;) to produce the complex integrated applications enabled by HPCC. The rst column of Table4 contains the area label and some sample applications. Algorithmic and other comments are in column two.... In PAGE 15: ... Our Caltech work was mainly on the hypercube, but the total of 300 references used in original classi cation covered work on the Butter y, transputers, the SIMD Connection Machine, and DAP. We originally iden- ti ed three temporal structures and one especially important (as it was so simple) spatial structure, which are the rst four entries in Table4 . Chap- ter 3 of [Fox:94a] describes a \complex systems quot; approach to computation and introduces the spatial and temporal structure of problems and comput- ers.... In PAGE 16: ... This is important in determing the performance, as shown in Chapter 3 of [Fox:94a] of an implementation, but it does not a ect the broad software issues discussed here. In Table4 , we only single out one special spatial structure, \embarrassingly parallel, quot; where there is little or no connection between the individual parallel program components. For embarrassingly parallel problems, illustrated in Figure 4, the synchronization (both soft- ware and hardware) issues are greatly simpli ed.... In PAGE 23: ... Each asynchronous task is now a synchronous or loosely synchronous mod- estly parallel evaluation of a given chess position. There were a few examples mentioned above of metaproblems in our orig- inal survey, but a major part of Table4 , from our New York State activity,... In PAGE 34: ...4 Summary Each of three case studies illustrates how di erent applications and di erent numerical approaches to a given problem, lead to very di erent problem architectures and correspondingly the needed software support. Although our discussion is not complete, we do think that it is quite typical, and that a similar situation is seen in the other applications of Table4 , and summarized in the last two columns.... ..."
Cited by 8
Table 4: Industrial HPCC Applications 14 to 18: Information Analysis|\DataMining quot; Application Area Problem Machine
1995
"... In PAGE 8: ...Table4 : Industrial HPCC Applications 1 to 5: SIMULATION Application Area Problem Machine Item and Examples Comments and Software 1 Computational PDE, FEM SIMD, MIMD for Fluid Dynamics Turbulence irregular adaptive Aerospace Mesh Generation HPF(+) but Military, Civilian Unclear for Vehicles adaptive irregular Propulsion mesh 2 Structural PDE, FEM MIMD as complex Dynamics Dominated by geometry Vendor Codes such HPF(+) as NASTRAN 3 Electromagnetic PDE solved by Simulation moment method SIMD Antenna Design Matrix solve HPF Stealth Vehicles dominates Noise in high Newer FEM and SIMD, MIMD frequency circuits FD Methods? HPF(+) Mobile Phones Also fast multipole 4 Scheduling Expert Systems MIMD Manufacturing and/or (unclear Speedup) Transportation AsyncSoft (Dairy delivery to Neural Networks SIMD Military deployment) Simulated annealing HPF University Classes Linear Programming MIMD Airline Scheduling (hard sparse matrix) HPF+? of crews, planes in static or dynamic (Syracuse snow storm) cases 5 Environmental PDE, FD, FEM SIMD but Modeling| Sensitivity to MIMD for Earth/Ocean/Atmos- Data irregular adaptive pheric Simulation mesh HPF(+) except this unclear for adaptive irregular mesh... In PAGE 9: ...Table4 : Industrial HPCC Applications 6 to 10: SIMULATION Application Area Problem Machine Item and Examples Comments and Software 6 Environmental Empirical Models Some SIMD but Phenomenology Monte Carlo and MIMD more |Complex Systems, Histograms natural (Lead Concentration HPF in blood) 7 Basic Chemistry Calculate Matrix Probably SIMD Chemical Potentials Elements with perhaps Elemental Reaction Matrix Eigenvalue SIMD possible Dynamics determination, HPF Inversion, Multiplication 8 Molecular Dynamics Particle Dynamics HPF(+) except in Physics amp; Chemistry with irregular need MPF for Biochemistry cuto forces fast multipole Discrete Simulation Fast Multipole Monte Carlo for Methods CFD (DSMC) Mix of PDE and Particle in the Cell Particle methods (PIC) in PIC and DSMC 9 Economic Modelling Single nancial Real Time instrument by SIMD, HPF Optimization Monte Carlo Mortgaged backed Full Simulations MIMD or SIMD Securities of complete with Integration Option Pricing portfolios Software 10 Network Simulations Sparse matrices MIMD Electrical Circuit Zero structure HPF for matrix Microwave and VLSI de ned by elements Biological (neural) connectivity MPF or library Circuit for matrix solve... In PAGE 10: ...Table4 : Industrial HPCC Applications 11 to 13: SIMULATION Application Area Problem Machine Item and Examples Comments and Software 11 Particle Transport Monte Carlo Methods Problems as in neutron MIMD transport for (nuclear) HPF explosion simulations 12 Graphics (rendering) HPF for simple ray Hollywood Several Operational tracing but MPF Virtual Reality Parallel Ray tracers for best algorithms Distributed model MIMD amp; Asyncsoft hard for distributed database 13 Integrated Complex Event Driven Timewarp or other System Simulations (ED) and Event Driven Defense (SIMNET, Time stepped Simulation needs Flight Simulators) (TS) simulations Appropriate Education Virtual Reality Asyncsoft (SIMCITY) Interfaces Integration Multimedia/VR in Database backends Software Entertainment Interactive Database Multiuser Virtual HPF+ for TS Worlds Simulation Chemical and Nuclear Plants... In PAGE 12: ...Table4 : Industrial HPCC Applications 19 to 22 for Information Access InfoVision|Information, Video, Imagery and Simulation on Demand Application Problem Machine amp; Item Area Comments Structure Software 19 Transaction Database-most Embarrassingly MIMD Processing transactions short. Parallel Database ATM As add \value quot; (automatic this becomes teller machine) Informationintegration 20 Collaboration Research Center or Asynchronous High Speed Telemedicine doctor(s)|patient Network Collaboratory interaction without for Research regard to physical Education location Business 21 Text on Multimedia Embarrassingly MIMD Demand database Parallel Database Digital (existing) (see areas 22, 23) libraries Full text search ERIC Education database, United Nations- Worldwide newspapers 22 Video on Multimedia Embarrassingly MIMD Demand Database Parallel for Database Movies, News Interactive VCR, multiple Users Video Editing (CNN Newsource Video Browsing, Software amp; Newsroom), Link of Interesting Current cable, video and text parallel United Nations- database compression SIMD Policy Support compression... In PAGE 13: ...Table4 : Industrial HPCC Applications 23 to 24 for Information Access InfoVision|Information, Video, Imagery and Simulation on Demand Application Problem Machine amp; Item Area Comments Structure Software 23 Imagery on Multimedia Metaproblem MIMD but Demand database Embarrassingly much SIMD Kodak GIODE Image Parallel plus image \clip art quot; on Understanding for Loosely analysis demand Content searching Synchronous Medical images and (terrain) Image Satellite images medical feature Understanding identi cation 24 Simulation on Multimedia map Synchronous SIMD terrain Demand database terrain engine (parallel Education, Generalized rendering with rendering) Tourism, City ight simulator Asynchronous MIMD planning, Geographical Hypermedia database Defense Information Integration mission planning System software... In PAGE 14: ...Table4 : Information Integration Applications 25 to 28 These involve combinations of Information Production, analysis, Access and Dissemination and thus need the Integration of the various Software and Machines Architecture Issues discussed under previous application areas. Sometimes Called System of Systems 25: Military and Civilian Command and Control (C2, C3, C4I : : :) Battle Management, Command, Control, Communication, Intelligence and Surveillance (BMC3IS) Military Decision Support Crisis Management|Police and other Government Operations SIMNET simulates this and with people and computers in the loop has many of same issues 26 to 28: Applications of InfoVision Services Generalize Compuserve, Prodigy, America Online, Dialog and Other In- formation Services 26: Decision Support for Society Community Information Systems Travel and Generalized Yellow Page Services 27: Business Decision Support|One example is: Health Care with Image and Video databases supporting telemedicine 28: Public Administration and Political Decision Support Government Information Systems Maxwell School at Syracuse University teaches use of realtime video to aid world wide decisions (United Nations)... In PAGE 15: ...Table4 : Information Integration Applications 29 to 33 29: Real-Time Control Systems Robotics uses Imagery to make decisions (control vehicles) Energy management controls power use and generation 30: Electronic Banking Requires Security, Privacy, Electronic Cash, etc. 31: Electronic Shopping 32: Agile Manufacturing|Multidisciplinary Design and Concurrent Engineering Combines CAD with Applications 1 to 3 Requires major changes to Manufacturing Infrastructure and Approach 33: Education InfoMall Living Textbook|6 Schools on ATM network linked to HPCC InfoVision Servers at NPAC [Mills:95a] Table 1 describes the general guidelines used in organizing Table 4.... In PAGE 15: ... 29: Real-Time Control Systems Robotics uses Imagery to make decisions (control vehicles) Energy management controls power use and generation 30: Electronic Banking Requires Security, Privacy, Electronic Cash, etc. 31: Electronic Shopping 32: Agile Manufacturing|Multidisciplinary Design and Concurrent Engineering Combines CAD with Applications 1 to 3 Requires major changes to Manufacturing Infrastructure and Approach 33: Education InfoMall Living Textbook|6 Schools on ATM network linked to HPCC InfoVision Servers at NPAC [Mills:95a] Table 1 describes the general guidelines used in organizing Table4 . Note that we did not directly cover academic areas, and a more complete list (which included our industrial table) was produced by the Peta ops meeting [Peta:94a].... In PAGE 15: ... Here, \Info quot; refers to the information based application focus and \Mall quot; to the use of a virtual corporation (groups of \storeholders quot;) to produce the complex integrated applications enabled by HPCC. The rst column of Table4 contains the area label and some sample applications. Algorithmic and other comments are in column two.... In PAGE 16: ... Our Caltech work was mainly on the hypercube, but the total of 300 references used in original classi cation covered work on the Butter y, transputers, the SIMD Connection Machine, and DAP. We originally iden- ti ed three temporal structures and one especially important (as it was so simple) spatial structure, which are the rst four entries in Table4 . Chap- ter 3 of [Fox:94a] describes a \complex systems quot; approach to computation and introduces the spatial and temporal structure of problems and comput- ers.... In PAGE 17: ... This is important in determing the performance, as shown in Chapter 3 of [Fox:94a] of an implementation, but it does not a ect the broad software issues discussed here. In Table4 , we only single out one special spatial structure, \embarrassingly parallel, quot; where there is little or no connection between the individual parallel program components. For embarrassingly parallel problems, illustrated in Figure 4, the synchronization (both soft- ware and hardware) issues are greatly simpli ed.... In PAGE 24: ... Each asynchronous task is now a synchronous or loosely synchronous mod- estly parallel evaluation of a given chess position. There were a few examples mentioned above of metaproblems in our orig- inal survey, but a major part of Table4 , from our New York State activity,... In PAGE 35: ...4 Summary Each of three case studies illustrates how di erent applications and di erent numerical approaches to a given problem, lead to very di erent problem architectures and correspondingly the needed software support. Although our discussion is not complete, we do think that it is quite typical, and that a similar situation is seen in the other applications of Table4 , and summarized in the last two columns.... ..."
Cited by 8
Table 3. Results of general and exception rule mining.
2000
"... In PAGE 15: ... In particular, they find the exception rules e specially helpful in understanding some of the special subpopulation that exhibits trends which are contrary to the main population. Table3 gives a summary of the number of general and exception rules discovered . In the year 1993 , the decision tree did not produce any significant rules , and hence there is no general rule and exception .... ..."
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Table 1: Common Data Mining Tasks and the Nature
"... In PAGE 4: ... Both of these regions are iso- thetic. As shown in Table1 , there are some commonly used mining tasks that produce regions that are more complex than isothetic, and require their membership criteria to be captured as general linear constraints #28e.... In PAGE 9: ... Examples of #16 include decision tree, fre- quent sets, data cube, depth contour, etc. Wemay re- gard p asanumber that speci#0Ces whether the desired intensional dimension is a decision tree, a depth con- tour, or any task mentioned in Table1 . For clarity,we use short strings instead of numbers in our examples.... In PAGE 11: ... The main problems involving constraints which di- rectly impact the e#0Eciency of dimension algebra at a logical level, are testing constraint implication #28and equivalence#29, consistency checking, and constraint sim- pli#0Ccation. It is important to note that, as shown in Table1 , numerous existing data mining tasks produce isothetic regions, for which all three problems can be solved e#0Eciently. Speci#0Ccally, in this case, the con- straints are of the form A i #12c, #12 being #14 or #15, and the problems can be solved in linear time.... ..."
Table 3 shows examples of how this metadata can help detecting data quality problems. Problems Metadata Examples/Heuristics
2000
"... In PAGE 6: ... Table3 . Examples for the use of reengineered metadata to address data quality problems Data mining helps discover specific data patterns in large data sets, e.... ..."
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Table 4 shows the prediction results for the heart problem. This application demonstrates not only the ability of teams in real data-mining but also in noisy problem enviroments since many data attributes are missing or are unknown. The difierence in prediction error between GP and TeamGP is about 2% which is signiflcant in the respective real problem domain. The problem structure does not ofier many possibilities for specialization, espe- cially in case of the winner-takes-all approaches which do not generalize signiflcantly better here than the standard approach. The main beneflt of the other combination methods seems to be that they improve fltness and generalization quality for the noisy data by a collective decision making of more than one team program.
2001
"... In PAGE 18: ...2 (0.32) Table4 : Heart: Classiflcation error (CE) in percent, averaged over 60 runs. Statistical standard error in parentheses.... ..."
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