عنوان

Data science and big data computing :frameworks and methodologies

English

Data science and big data computing :frameworks and methodologies

Cham

Springer

c2016

xxi, 319 p.

editor: Zaigham Mahmood

1

Part I: Data Science Applications and Scenarios An Interoperability Framework and Distributed Platform for Fast Data ApplicationsJos Carlos Martins Delgado Complex Event Processing Framework for Big Data ApplicationsRenta Chintala Bhargavi Agglomerative Approaches for Partitioning of Networks in Big Data ScenariosAnupam Biswas, Gourav Arora, Gaurav Tiwari, Srijan Khare, Vyankatesh Agrawal and Bhaskar Biswas Identifying Minimum-Sized Influential Vertices on Large-Scale Weighted Graphs: A Big Data PerspectiveYing Xie, Jing )Selena( He and Vijay V. Raghavan Part II: Big Data Modelling and Frameworks A Unified Approach to Data Modelling and Management in Big Data EraCatalin Negru, Florin Pop, Mariana Mocanu and Valentin Cristea Interfacing Physical and Cyber Worlds: A Big Data PerspectiveZartasha Baloch, Faisal Karim Shaikh and Mukhtiar A. Unar Distributed Platforms and Cloud Services: Enabling Machine Learning for Big DataDaniel Pop, Gabriel Iuhasz and Dana Petcu An Analytics Driven Approach to Identify Duplicate Bug Records in Large Data RepositoriesAnjaneyulu Pasala, Sarbendu Guha, Gopichand Agnihotram, Satya Prateek B and Srinivas Padmanabhuni Part III: Big Data Tools and Analytics Large Scale Data Analytics Tools: Apache Hive, Pig and HBaseN. Maheswari and M. Sivagami Big Data Analytics: Enabling Technologies and ToolsMohanavadivu Periasamy and Pethuru Raj A Framework for Data Mining and Knowledge Discovery in Cloud ComputingDerya Birant and Pelin Y ld r m Feature Selection for Adaptive Decision Making in Big Data AnalyticsJaya Sil and Asit Kumar Das Social Impact and Social Media Analysis Relating to Big DataNirmala Dorasamy and Nata a Pomazalov

، Computer science

، Data mining

، Big data

AU

AU Mahmood, Zaigham