Future Data and Security Engineering
Second International Conference, FDSE 2015, Ho Chi Minh City, Vietnam, November 23-25, 2015, Proceedings
By Tran Khanh Dang, Roland Wagner, Erich J. Neuhold, Makoto Takizawa, Josef Küng and Nam Thoai
"Future Data and Security Engineering" is published by Springer in Nov 10, 2015 - Cham and it has 336 pages.
“Future Data and Security Engineering” Metadata:
- Title: ➤ Future Data and Security Engineering
- Authors: ➤ Tran Khanh DangRoland WagnerErich J. NeuholdMakoto TakizawaJosef KüngNam Thoai
- Number of Pages: 336
- Publisher: Springer
- Publish Date: Nov 10, 2015
- Publish Location: Cham
“Future Data and Security Engineering” Subjects and Themes:
- Subjects: ➤ Computer security - Data encryption (computer science) - Data mining - Internet - Database management - Information retrieval - Information organization - Computer science - Data protection - Computer software - Information storage and retrieval systems - Information Systems - Management of Computing and Information Systems - Systems and Data Security - Data Encryption - Algorithm Analysis and Problem Complexity
Edition Specifications:
- Format: paperback
Edition Identifiers:
- The Open Library ID: OL28026084M - OL20673185W
- ISBN-13: 9783319261348 - 9783319261355
- ISBN-10: 3319261347
- All ISBNs: 3319261347 - 9783319261348 - 9783319261355
AI-generated Review of “Future Data and Security Engineering”:
"Future Data and Security Engineering" Description:
Open Data:
Intro -- Preface -- Organization -- Contents -- Big Data Analytics and Massive Dataset Mining -- Random Local SVMs for Classifying Large Datasets -- 1 Introduction -- 2 Support Vector Machines -- 3 Parallel Ensemble Learning Algorithm of Random Local Support Vector Machines -- 4 Evaluation -- 5 Discussion on Related Works -- 6 Conclusion and Future Works -- References -- An Efficient Document Indexing-Based Similarity Search in Large Datasets -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 3.1 Similarity Search -- 3.2 MapReduce Paradigm -- 4 The Proposed Methods -- 4.1 The Clustering Scheme -- 4.2 Redundancy-Free Compatibility -- 4.3 Filtering Strategies -- 4.4 Examples on the Fly -- 5 Emperical Experiments -- 5.1 Environment Settings -- 5.2 Evaluation -- 6 Summary -- Acknowledgements -- References -- Using Local Rules in Random Forests of Decision Trees -- 1 Introduction -- 2 Random Forest Algorithm Using Local Labeling Rules -- 2.1 Random Forests -- 2.2 Local Labeling Rules in Decision Forests -- 3 Evaluation -- 4 Discussion on Related Work -- 5 Conclusion and Future Works -- References -- A Term Weighting Scheme Approach for Vietnamese Text Classification -- Abstract -- 1 Introduction -- 2 Background and Related Works -- 2.1 Related Works -- 2.2 Background -- 3 Our Proposed Term Weighting Method -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Evaluation Methodology -- 4.3 Results -- 5 Conclusion -- Acknowledgment -- References -- Security and Privacy Engineering -- Fault Data Analytics Using Decision Tree for Fault Detection -- 1 Introduction -- 2 Related Work -- 3 CART Approach -- 3.1 Entropy Splitting Rule -- 3.2 Tree Growing Process -- 4 Fault Data Analysis -- 4.1 Bug Data -- 4.2 Data Processing -- 4.3 Tree Construction -- 5 Evaluation -- 6 Conclusions -- References
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