Human-Centered e-BusinessSpringer Science & Business Media, 2003. gada 31. maijs - 315 lappuses Human-Centered e-Business focuses on analysis, design and development of human-centered e-business systems. The authors illustrate the benefits of the human-centered approach in intelligent e-sales recruitment application, integrating data mining technology with decision support model for profiling transaction behavior of internet banking customers, user-centered context dependent data organization using XML, knowledge management, and optimizing the search process through human evaluation in an intelligent interactive multimedia application. The applications described in this work, facilitates both e-business analysis from a business professional's perspective, and human-centered system design from a system development perspective. These applications employ a range of internet and soft computing technologies. |
Saturs
WHY HUMANCENTERED eBUSINESS? | 1 |
12 eBusiness and eCommerce | 2 |
13 Converging Trends Towards HumanCenteredness | 4 |
14 TechnologyCenteredness vs Human Centeredness | 5 |
15 HumanCentered Approach | 8 |
16 Organization Levels and eBusiness | 10 |
References | 12 |
eBUSINESS CONCEPTS AND TECHNOLOGIES | 13 |
563 Multimedia Agents | 155 |
57 Emergent Characteristics of HCVM | 156 |
571 Architectural Characteristics | 157 |
References | 160 |
eSALES RECRUITMENT | 161 |
63 Information Technology and Recruitment | 162 |
64 Activity Centered eBusiness Analysis of Sales Recruitment Activity | 163 |
642 Performance Analysis of Sales Recruitment Activity | 166 |
222 Decision Support Systems | 14 |
224 Knowledge Management Systems | 15 |
232 ValueChain Integration | 16 |
24 eBusiness Models | 17 |
242 Content Provider | 18 |
244 Intermediary | 19 |
247 Virtual Community | 20 |
25 Internet and Web Technologies | 22 |
252The eXtensible Markup Language | 23 |
2521 XML Namespaces | 27 |
2522 XMLbased Agent Systems Development | 29 |
2611 Symbolic Knowledge Representation | 30 |
2612 Rule Based Architecture | 33 |
2613 Rule and Frame Object Based Architecture | 34 |
2615 Blackboard Architecture | 35 |
2616 Some Limitations of Expert System Architectures | 36 |
263Artificial Neural Networks | 37 |
2631 Perceptron | 38 |
2632 Multilayer Perceptrons | 40 |
2633 Radial Basis Function Net | 43 |
2634 Kohonen Networks | 44 |
264 Fuzzy Systems | 46 |
2641 Fuzzy Sets | 47 |
2643 Fuzzy Inferencing and Rule Evaluation | 48 |
2644 Defuzzification of Outputs | 49 |
265 Genetic Algorithms | 51 |
2652 Reproduction | 52 |
265 J Crossover | 53 |
2655 The Stopping Criterion | 54 |
266 Intelligent Fusion Transformation and Combination | 55 |
271ObjectOriented Software Engineering | 56 |
2712 Encapsulation | 57 |
28 Multimedia | 59 |
29 Summary | 60 |
References | 61 |
CONVERGING TRENDS TOWARDS HUMANCENTEREDNES AND ENABLING THEORIES | 65 |
321 eBusiness and HumanCenteredness | 66 |
322 Intelligent Systems and HumanCenteredness | 68 |
322 Software Engineering and HumanCenteredness | 72 |
323 Multimedia Databases and HumanCenteredness | 74 |
325 Data Mining and HumanCenteredness | 76 |
327 HumanComputer Interaction and HumanCenteredness | 78 |
331 Semiotic Theory Language of Signs | 79 |
3311 Rhematic Knowledge | 82 |
3312 Dicent Knowledge | 83 |
332 Cognitive Science Theories | 84 |
3322 Radical Approach | 85 |
3323 Situated Cognition | 86 |
3324 Distributed Cognition | 88 |
333 Activity Theory | 89 |
334 Workplace Theory | 92 |
34 Discussion | 93 |
35 Summary | 95 |
HUMANCENTERED eBUSINESS SYSTEM DEVELOPMENT FRAMEWORK | 103 |
43 External and Internal Planes of HumanCentered Framework | 104 |
44 Components of the HumanCentered eBusiness System Development Framework | 105 |
45 ActivityCentered eBusiness Analysis Component | 106 |
451Problem Definition and Scope | 107 |
452 Performance Analysis of System Components | 109 |
453 Context Analysis of System Components | 110 |
4533 Product Context | 111 |
4535 Tool Context | 112 |
456 Task Product Transition Network | 113 |
457 eBusiness Infrastructure Analysis | 114 |
47 Summary | 118 |
References | 119 |
HUMANCENTERED VIRTUAL MACHINE | 121 |
521Definition of Terms Used | 123 |
522 Problem Solving Adapters | 125 |
5223 Control Phase Adapter | 130 |
5225 Postprocessing Phase Adapter | 138 |
53 HumanCentered Criteria and Problem Solving Ontology | 139 |
54 Transformation Agent Component | 140 |
55 Multimedia Interpretation Component | 144 |
551 Data Content Analysis | 145 |
552 Media Media Expression and Ornamentation Selection | 146 |
553 Media Presentation Design and Coordination | 149 |
561 Patient Symptom Content Analysis | 151 |
562 Media Media Expression and Ornamentation Selection | 153 |
643 Context Analysis of the Sales Recruitment Activity | 167 |
644 Alternative eBuslness System Goals and Tasks | 170 |
645 HumanTaskTool Diagram | 172 |
646 Task Product Transition Network | 174 |
65 HumanCentered Activity Model | 175 |
651 Mapping Decomposition Adapter to SRA Tasks | 176 |
652 Mapping Control Phase and Decision Phase Adapter to SRA Tasks | 177 |
66 Implementation and Results | 180 |
661 ES Model of Behavior Categorization | 181 |
662 Predictive Model of Behavior Categorization | 184 |
663 Behavior Profiling and Benchmarking | 185 |
65 Summary | 188 |
CUSTOMER RELATIONSHIP MANAGEMENT AND eBANKING | 191 |
73 Data Mining Algorithms | 193 |
74 Data Mining and the Internet | 195 |
741 Internet Content Mining | 196 |
7412 AgentBased Approach | 197 |
742 Internet Usage Mining | 198 |
75 Multilayered Componentbased MultiAgent Distributed Data Mining Architecture | 199 |
76 Application In eBanking | 200 |
761 CRM Model of eBanking Manager | 201 |
7612 Control Phase | 202 |
7613 Decision Phase | 204 |
762 Agent Design and Implementation | 205 |
77 Data Mining Implementation Results | 208 |
771 Transaction Frequency | 209 |
772 Product Similarity | 210 |
773 Customer Association | 212 |
References | 213 |
HCVM BASED CONTEXTDEPENDENT DATA ORGANIZATION FOR eCOMMERCE | 217 |
82 Contextdependent Data Management | 219 |
821 Context Representation in ECommerce Transactions | 220 |
83 Context Modeling in XML | 223 |
831 Using the Simple Object Access Protocol SOAP for Context Initialization | 227 |
832 Contextaware User Interface Based on HCVM | 229 |
84 Flexible Access to Context Information | 230 |
841 Fuzzy Closure Computation | 234 |
842 Query Execution | 236 |
85 Sample Interaction | 237 |
86 Summary | 239 |
HUMANCENTERED KNOWLEDGE MANAGEMENT | 243 |
94 The Regional Innovation Leadership RIL Cycle | 245 |
951 Knowledge Hubs Actors | 246 |
952 Cluster of Services | 247 |
97 Knowledge Hubs Content Management System | 248 |
971 Spider and Validator Agents | 249 |
98 Decision Support and Navigation Agents | 253 |
99 Summary | 254 |
References | 255 |
HYPERMEDIA INFORMATION SYSTEMS | 257 |
102 Background | 258 |
103 Character of Multimedia Data | 259 |
105 ContentBased Retrieval Indexing | 261 |
1052 Image and Semcon Matching | 264 |
1053 Generic Image Model | 267 |
1054 Shape Matching | 268 |
1055 Color Matching | 269 |
106 Bridging the Semantic Gap | 274 |
1062 User Semantics and HCVM | 276 |
107 Commercial Systems for Hypermedia Information Systems | 277 |
108 Summary | 278 |
HUMANCENTERED INTELLIGENT WEB BASED MISSING PERSON CLOTHING IDENTIFICATION SYSTEM | 283 |
1121 Vector Space Model | 284 |
114 Design Components Of Clothing Identification System | 287 |
11412 Display AH Shirt | 291 |
11413 User Details and Relevance Feedback | 292 |
11422 Reproduction | 293 |
11423 Crossover | 294 |
11424 Mutation | 295 |
115 Implementation and Results | 297 |
1152 Data Structures | 298 |
1153 Relevance Feedback | 299 |
1153 Converting Population to Images | 300 |
1154 Starting the Process | 301 |
1157 User Feedback and Show Filenames | 302 |
References | 304 |
INDEX | 305 |
Citi izdevumi - Skatīt visu
Human-Centered e-Business Rajiv Khosla,Ernesto Damiani,William Grosky Ierobežota priekšskatīšana - 2012 |
Human-Centered e-Business Rajiv Khosla,Ernesto Damiani,William Grosky Priekšskatījums nav pieejams - 2012 |
Bieži izmantoti vārdi un frāzes
actions activity adapter agent algorithms analysis application approach architecture areas artifacts associated behavior candidate chapter characteristics clustering cognitive color communication complex component concepts context data mining database decision defined definition described determine dimensions distributed document domain e-business ELEMENT engineering environment example external function fuzzy goals HCVM human human-centered indexing input integration intelligent interaction internal Internet interpretation involves knowledge language layer learning methods multimedia namely neural object ontology operations organization outlined output patterns performance phase problem solving query recruitment relationship relevant representation represented retrieval rule scale selection selling semantic shape shirt shown in Figure similar situations specific strategy structure symbolic tasks techniques theories tool transaction transformation types various weights
Atsauces uz šo grāmatu
Research Directions in Data and Applications Security XVIII: IFIP TC11 ... Csilla Farkas,Pierangela Samarati Priekšskatījums nav pieejams - 2004 |