Data mining : a heuristic approach

Developments In Managing Innovation, Knowledge And E-business / Benn Lawson, Danny Samson -- Sources Of Knowledge Acquisition By U.s. Managers: An Empirical Analysis / Jaideep Motwani, Pradeep Gopalakrishma, Ram Subramanian -- Information Systems And Business Strategy: A Concurrent Planning Model / Antonio Torres-perez, Isidre March-chorda -- Integrated Qfd And Knowledge Management System For The Development Of Common Product Platform / Walter W.c. Chung, Colin K.s. Tam, Michael F.s. Chan -- An Expanded Model Of The Effects Of Organizational Culture Upon The Acceptance Of Knowldege Management / Nancy C. Shaw, Francis D. Tuggle -- Information-based Integration For Complex Systems / E. Szczerbicki -- An Experimental Analysis Of The Effectiveness And Efficiency Of Teams With Partial Problem Domain Knowledge / Dinesh A. Mirchandani, Jaideep Motwani -- Collaboration In The Large: Using Videoconferencing To Facilitate Large-group Interaction / Diane H. Sonnewald [and Others] --^ A Dynamic Perspective On Knowledge Creation In Virtual Teams -- In A Search For New Insights / Violina Ratcheva -- The Impact Of Trust In Virtual Enterprises / T.t. Wong, Henry C.w. Lau -- Market Of Resources As An Environment For Agile/virtual Enterprise Dynamic Integration And For Business Alignment / Maria Manuela Cunha, Goran D. Putnik, A. Gunasekaran -- Managing Business-consumer Interaction In The E-world / Sushil K. Sharma, Jatinder N.d. Gupta -- Electronic Money And Payment Systems / Santosh K. Misra, Jayavel Sounderpandian -- A Managerial Perspective On E-commerce: Adoption, Diffusion And Cultural Issues / Thuong T. Le, S. Subba Rao, Dothang Truong -- Human And Social Perspectives In Information Technology: An Examination Of Fraud On The Internet / C. Richard Baker -- The Role Of Trust In Information Technology Management / István Mezgár, Zoltán Kincses -- Inexperienced Software Team And Global Software Team / Kim Man Lui, Keith C.c. Chan --^ The Knowledge Edge: Knowledge Management And Social Learning In Military Settings / Leoni Warne [and Others]. [edited By] Angappa Gunasekaran And Omar Khalil, Syed Mahbubur Rahman. Includes Bibliographical References And Index. Data Mining: Opportunities and Challenges......Page 2 Copyright......Page 3 Table of Contents......Page 5 Preface......Page 8 References......Page 13 Acknowledgments......Page 14 INTRODUCTION......Page 16 SCHOOLS OF STATISTICS......Page 17 DATA MODEL......Page 21 LOCAL GRAPHICAL MODEL CHOICE......Page 25 GLOBAL GRAPHICAL MODEL CHOICE......Page 30 NON- CATEGORICAL VARIABLES......Page 31 CASE 1: PERSONALIZED MEDIA DISTRIBUTION......Page 35 CASE 2: SCHIZOPHRENIA RESEARCH ̈CCAUSALITY IN COMPLEX SYSTEMS......Page 37 CONCLUSIONS......Page 39 REFERENCES......Page 40 ABSTRACT......Page 42 INTRODUCTION......Page 43 BACKGROUND......Page 46 METHODOLOGIES......Page 55 RESULTS......Page 61 ACKNOWLEDGMENTS......Page 65 REFERENCES......Page 66 ABSTRACT......Page 70 INTRODUCTION......Page 71 COOPERATIVE DATA MINING......Page 72 VISUAL DATA MINING......Page 74 THREE- DIMENSIONAL VISUALIZATION,VIRTUAL REALITY AND DATA MINING......Page 83 CONCLUSIONS......Page 90 REFERENCES......Page 91 ABSTRACT......Page 95 INTRODUCTION......Page 96 EVOLUTIONARY LOCAL SELECTION ALGORITHMS ( ELSA)......Page 97 FEATURE SELECTION IN SUPERVISED LEARNING......Page 99 FEATURE SELECTION IN UNSUPERVISED LEARNING......Page 104 FEATURE SELECTION FOR ENSEMBLES......Page 111 CONCLUSIONS......Page 117 REFERENCES......Page 118 ABSTRACT......Page 121 INTRODUCTION......Page 122 PARALLEL AND DISTRIBUTED DATA MINING......Page 123 STRUCTURED PARALLEL PROGRAMMING......Page 125 STRUCTURED PARALLEL DATA MINING ALGORITHMS......Page 130 ADVANTAGES OF STRUCTURE PARALLELISM......Page 152 CONCLUSIONS......Page 153 REFERENCES......Page 154 INTRODUCTION......Page 157 ROUGH SET THEORY......Page 162 VARIABLE PRECISION ROUGH SET MODEL ( VPRSM)......Page 168 DATA MINING SYSTEM LERS......Page 175 APPLICATIONS......Page 183 CONCLUSIONS......Page 184 REFERENCES......Page 185 THE IMPACT OF MISSING DATA......Page 189 DATA MINING WITH INCONSISTENT DATA/ MISSING DATA......Page 193 METHODS OF ADDRESSING MISSING DATA......Page 196 THE IMPACT OF MISSING DATA ON DATA- MINING ALGORITHMS......Page 202 FUTURE TRENDS......Page 206 CONCLUSIONS......Page 208 REFERENCES......Page 209 ABSTRACT......Page 214 INTRODUCTION......Page 215 RELATED WORK......Page 216 GENERATING CLUSTERS......Page 218 DEVELOPING THEMATIC HIERARCHIES FOR TEXT DOCUMENTS......Page 222 EXPERIMENTAL RESULTS......Page 227 FUTURE WORK......Page 231 REFERENCES......Page 232 INTRODUCTION......Page 235 ORGANIZATIONAL ISSUES......Page 236 STATISTICAL ISSUES......Page 240 DATA ACCURACY AND STANDARDIZATION......Page 243 TECHNICAL ISSUES......Page 247 REFERENCES......Page 251 ABSTRACT......Page 254 INTRODUCTION......Page 255 MOTIVATION......Page 256 BASIC COST MODELS AND ESTIMATION MODELS......Page 258 APPLICATION TO THE DATA......Page 259 ESTIMATION CRITERION QUALITY ISSUES......Page 264 LIMITATIONS......Page 267 EXTENSIONS TO OTHER BASIC COST MODELS......Page 268 DATA- MINING APPLICATIONS AND CONSIDERATIONS......Page 270 CONCLUSIONS......Page 271 REFERENCES......Page 272 APPENDIX......Page 273 ABSTRACT......Page 275 DATA MINING, CLASSIFICATION AND SUPERVISED LEARNING......Page 276 THE BAYESIAN APPROACH TO PROBABILITY......Page 277 BAYESIAN CLASSIFICATION......Page 281 BAYESIAN BELIEF NETWORKS......Page 284 MARKOV CHAIN MONTE CARLO TECHNIQUES......Page 289 CONCLUDING REMARKS......Page 290 REFERENCES......Page 291 INTRODUCTION......Page 293 RELATED WORK......Page 295 MINING NEWSGROUPS¡ ̄ EXPERTISE......Page 298 MINING FAQS FOR STRUCTURE......Page 300 EVALUATION......Page 307 FUTURE TRENDS......Page 308 CONCLUSION......Page 310 ENDNOTES......Page 311 REFERENCES......Page 312 APPENDIX......Page 314 INTRODUCTION......Page 316 BACKGROUND......Page 318 QUERY- BY- STRUCTURE SYSTEMS......Page 323 FUTURE TRENDS......Page 335 CONCLUSION......Page 336 REFERENCES......Page 337 ABSTRACT......Page 338 INTRODUCTION......Page 339 METHODOLOGY......Page 341 COMPANIES INCLUDED......Page 348 CONSTRUCTING THE MAPS......Page 349 RESULTS......Page 353 CONCLUSIONS......Page 359 FUTURE RESEARCH IN THIS AREA......Page 360 REFERENCES......Page 361 APPENDIX:THE FEATURE PLANES OF THE FINAL MAP......Page 363 INTRODUCTION......Page 365 DATA MINING IN HEALTH CARE......Page 366 COMMUNITY HEALTH INFORMATION NETWORKS ( CHINS)......Page 367 FINDINGS USING A CASE METHODOLOGY......Page 370 HOW THE PLATFORM CAN BE USED......Page 374 DATA- MINING IMPLICATIONS:CONTROVERSIES AND ISSUES ASSOCIATED WITH CHINS......Page 376 REFERENCES......Page 378 INTRODUCTION......Page 381 BACKGROUND......Page 382 APPLYING DATA MINING TECHNIQUES TO HR INFORMATION SYSTEMS......Page 387 PRACTICAL APPLICATIONS OF DATA MINING HR INFORMATION......Page 393 CONCLUSIONS......Page 394 REFERENCES......Page 395 ABSTRACT......Page 397 INTRODUCTION......Page 398 DATA ENVELOPMENT ANALYSIS......Page 399 THE MODEL......Page 403 APPLICATION......Page 405 REFERENCES......Page 409 INTRODUCTION......Page 410 WHAT CAN BE INFERRED FROM DATA?......Page 412 ETHICAL ISSUES......Page 413 SOCIAL IMPLICATIONS......Page 416 LEGAL ISSUES......Page 423 FUTURE TRENDS......Page 431 CONCLUSION......Page 432 REFERENCES......Page 433 ABSTRACT......Page 436 INTRODUCTION......Page 437 USE OF DATA MINING IN DESIGNING THE SYSTEM KNOWLEDGE BASE......Page 438 USE OF DATA MINING IN DESIGNING THE LEARNING PROCESS......Page 441 MULTIAGENT- BASED ARCHITECTURE FOR THE DYNAMIC DSS......Page 448 CONCLUSIONS......Page 450 REFERENCES......Page 451 MAJOR TRENDS IN TECHNOLOGIES AND METHODS: WEB MINING......Page 452 TEXT DATA MINING ( TDM)......Page 455 UBIQUITOUS DM ( UDM)......Page 456 VISUAL DM......Page 457 SPATIAL AND GEOGRAPHIC DM......Page 458 DM TRENDS: METHODS AND TECHNIQUES......Page 459 DM FOR BIOINFORMATICS......Page 460 SUMMARY......Page 461 REFERENCES......Page 462 About the Authors......Page 468 Index......Page 477 The importance of knowledge and information technology management has been emphasized both by researchers and practitioners in order for companies to compete in the global market. Now such technologies have become crucial in a sense that there is a need to understand the business and operations strategies, as well as how the development of IT would contribute to knowledge management and therefore increase competitiveness. This book explores the human resource and social dimensions of knowledge and IT management, discusses the opportunities and major issues related to the management of people along the supply chain in Internet marketing, and provides an understanding of how the human resource and the IT management should complement each other for improved communication and competitiveness Real life problems are known to be messy, dynamic and multi-objective, and involve high levels of uncertainty and constraints. Because traditional problem-solving methods are no longer capable of handling this level of complexity, heuristic search methods have attracted increasing attention in recent years for solving such problems. Inspired by nature, biology, statistical mechanics, physics and neuroscience, heuristics techniques are used to solve many problems where traditional methods have failed. Data Mining: A Heuristic Approach will be a repository for the applications of these techniques in the area of data mining. This volume strives to explore the human resource and social dimensions of knowledge and IT management, to discuss the opportunities and major issues related to the management of people along the supply chain in Internet marketing.