| Description |
1 online resource |
| Series |
Intelligent systems series |
|
Intelligent systems series.
|
| Contents |
Front Cover; Big Data and Smart Service Systems; Copyright Page; Contents; List of Contributors; Introduction; Concepts; Age of Big Data; Service Science and System; Smart Service System; Techniques and Applications of Big Data; Characteristics of Big Data; Techniques of Big Data; Application of Big Data; The Framework of the Smart Service System; Example Analysis; Government Department; Public Health; Business; Social Management; Public Safety; Intelligent Transportation; Education Industry; Conclusions; References; 1 Vision-based vehicle queue length detection method and embedded platform |
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1.1 Introduction1.2 Embedded Hardware; 1.3 Algorithms of Video-Based Vehicle Queue Length Detection; 1.3.1 Vehicle Motion Detection; 1.3.2 Vehicle Presence Detection; 1.3.3 Threshold Selection; 1.3.4 Algorithm Summarization; 1.4 Program Process of DM642; 1.5 Evaluation; 1.6 Conclusions; Acknowledgment; References; 2 Improved information feedback in symmetric dual-channel traffic; 2.1 Introduction; 2.2 CAM and Information Feedback Strategies; 2.3 Simulation Results; 2.4 Conclusions; Acknowledgments; References; 3 Secure provable data possession for big data storage; 3.1 Introduction |
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3.2 Object Storage System Using SPDP3.2.1 Object Storage System; 3.2.2 Definition of SPDP; 3.2.3 SPDP Verification Algorithm; 3.2.4 Hierarchical Structure; 3.2.5 The Architecture for SPDP Model; 3.3 Security Analysis and Implementation; 3.3.1 SPDP Performance Analysis; 3.3.2 Approved Directories Optimization; 3.3.3 Secure Protection Strategy; 3.4 Robust Auditing With Authentication System; 3.4.1 Robust Auditing; 3.4.2 Authorized Server; 3.4.3 Large Object Processing; 3.5 Experimental Results; 3.6 Conclusions; References |
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4 The responsive tourism logistics from local public transport domain: the case of Pattaya city4.1 Introduction; 4.2 Previous Research; 4.3 Problems and Challenges; 4.4 Tourism Demand and Supply Characteristics; 4.5 Public Transportations; 4.6 Proximity of Tourist Attractions; 4.7 Capacity Flexibility Model for Responsive Transportations; 4.8 Capacity Considerations of Baht Bus Route; 4.9 Routing for DRT; References; 5 Smart cities, urban sensing, and big data: mining geo-location in social networks; 5.1 Introduction; 5.2 Systematic Literature Review; 5.2.1 Question Formulation |
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5.2.2 Source Selection5.2.3 Information Extraction and Result Summarization; 5.3 Discussion; 5.3.1 Data Sources; 5.3.1.1 Twitter; 5.3.1.2 Foursquare; 5.3.1.3 Others; 5.3.2 Mining Techniques; 5.3.2.1 k-Means; 5.3.2.2 Self-organizing map; 5.3.2.3 Density-based clustering; 5.3.2.4 Spectral clustering; 5.3.2.5 Mean-shift; 5.3.2.6 Others; 5.3.3 Use Scenarios; 5.3.3.1 Urban characterization; 5.3.3.2 Spatial discovery; 5.3.3.3 Exception alerting; 5.4 Big Data Approach: A Case Study; 5.5 Conclusion; References |
| Summary |
Big Data and Smart Service Systems presents the theories and applications regarding Big Data and smart service systems, data acquisition, smart cities, business decision-making support, and smart service design. The rapid development of computer and Internet technologies has led the world to the era of Big Data. Big Data technologies are widely used, which has brought unprecedented impacts on traditional industries and lifestyle. More and more governments, business sectors, and institutions begin to realize data is becoming the most valuable asset and its analysis is becoming the core competitiveness |
| Subject |
Big data.
|
|
COMPUTERS -- General.
|
|
Big data
|
| Form |
Electronic book
|
| Author |
Liu, Xiwei
|
|
Anand, Rangachari
|
|
Xiong, Gang
|
|
Shang, Xiuqin
|
|
Liu, Xiaoming
|
| ISBN |
9780128120408 |
|
0128120401 |
|
