| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015
|
| Descrizione fisica |
1 online resource (178 p.)
|
| Disciplina |
004
|
| Soggetto topico |
Mathematical statistics
Computer networks
Computer simulation
Computer science—Mathematics
Probability and Statistics in Computer Science
Computer Communication Networks
Simulation and Modeling
Math Applications in Computer Science
|
| ISBN |
3-319-25313-1
|
| Formato |
Materiale a stampa  |
| Livello bibliografico |
Monografia |
| Lingua di pubblicazione |
eng
|
| Nota di contenuto |
Foreword; Preface; Overview and Goals; Organisation and Features; Target Audiences; Suggested Uses; Acknowledgements; Contents; Contributors; Part I Theory; 1 Data Quality Monitoring of Cloud Databases Based on Data Quality SLAs; 1.1 Introduction and Summary; 1.2 Background; 1.2.1 Data Quality in the Context of Big Data; 1.2.2 Cloud Computing; 1.2.3 Data Quality Monitoring in the Cloud; 1.2.4 The Challenge of Specifying a DQSLA; 1.2.5 The Infrastructure Estimation Problem; 1.3 Proposed Solutions; 1.3.1 Data Quality SLA Formalization; 1.3.2 Examples of Data Quality SLAs
1.3.3 Data Quality-Aware Service Architecture1.4 Future Research Directions; 1.5 Conclusions; References; 2 Role and Importance of Semantic Search in Big Data Governance; 2.1 Introduction; 2.2 Big Data: Promises and Challenges; 2.3 Participatory Design for Big Data; 2.4 Self-Service Discovery; 2.5 Conclusion; References; 3 Multimedia Big Data: Content Analysis and Retrieval; 3.1 Introduction; 3.2 The MapReduce Framework and Multimedia Big Data; 3.2.1 Indexing; 3.2.2 Caveats on Indexing; 3.2.3 Multiple Multimedia Processing; 3.2.4 Additional Work Required?
5 Integrating Twitter Traffic Information with Kalman Filter Models for Public Transportation Vehicle Arrival Time Prediction5.1 Introduction; 5.2 Communication Platform on Twitter; 5.3 Communication for Data Collection on Twitter; 5.4 Event Detection and Analysis: Tweets Relating to Road Incidents; 5.4.1 Twitter Data: Incident Data Set; 5.5 Methodology; 5.5.1 Time Series and Temporal Analysis of Textual Twitter; 5.6 Proposed Refined Kalman Filter (KF) Model-Based System; 5.7 Conclusion; References; 6 Data Science and Big Data Analytics at Career Builder
6.1 Carotene: A Job Title Classification System6.1.1 Occupation Taxonomies; 6.1.2 The Architecture of Carotene; 6.1.2.1 Taxonomy Discovery Using Clustering; 6.1.2.2 Coarse-Level Classification: SOC Major Classifier; 6.1.2.3 Fine-Level Classification: Proximity-Based Classifier; 6.1.3 Experimental Results and Discussion; 6.2 CARBi: A Data Science Ecosystem; 6.2.1 Accessing CB Data and Services Using WebScalding; 6.2.2 ScriptDB: Managing Hadoop Jobs; References; 7 Extraction of Bayesian Networks from Large Unstructured Datasets; 7.1 Introduction; 7.2 Text Mining; 7.2.1 Text Mining Techniques
7.2.2 General Architecture and Various Components of Text Mining
|
| Record Nr. | UNINA-9910298964403321 |
Info
Big-Data Analytics and Cloud Computing : Theory, Algorithms and Applications / / edited by Marcello Trovati, Richard Hill, Ashiq Anjum, Shao Ying Zhu, Lu Liu
