Big Data Analytics First International Conference, BDA 2012, New Delhi, India, December 24-26, 2012. Proceedings /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Srinivasa, Srinath (Επιμελητής έκδοσης), Bhatnagar, Vasudha (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012.
• Σειρά: Lecture Notes in Computer Science, 7678
• Θέματα: Computer science.; Algorithms.; Database management.; Data mining.; Information storage and retrieval.; Artificial intelligence.; Computer Science.; Information Systems Applications (incl. Internet).; Artificial Intelligence (incl. Robotics).; Database Management.; Information Storage and Retrieval.; Data Mining and Knowledge Discovery.; Algorithm Analysis and Problem Complexity.

This book constitutes the refereed proceedings of the First International Conference on Big Data Analytics, BDA 2012, held in New Delhi, India, in December 2012. The 5 regular papers and 5 short papers presented were carefully reviewed and selected from 42 submissions. The volume also contains two t...

Πίνακας περιεχομένων:

• Perspectives on Big Data Analytics
• Scalable Analytics – Algorithms and Systems
• Big-Data – Theoretical, Engineering and Analytics Perspective
• Data Analytics Applications
• A Comparison of Statistical Machine Learning Methods in Heartbeat Detection and Classification
• Enhanced Query-By-Object Approach for Information Requirement Elicitation in Large Databases
• Cloud Computing and Big Data Analytics: What Is New from Databases Perspective?
• A Model of Virtual Crop Labs as a Cloud Computing Application for Enhancing Practical Agricultural Education
• Knowledge Discovery through Information Extraction
• Exploiting Schema and Documentation for Summarizing Relational Databases
• Faceted Browsing over Social Media
• Analog Textual Entailment and Spectral Clustering (ATESC) Based Summarization
• Economics of Gold Price Movement-Forecasting Analysis Using Macro-economic, Investor Fear and Investor Behavior Features
• Data Models in Analytics
• An Efficient Method of Building an Ensemble of Classifiers in Streaming Data
• I/O Efficient Algorithms for Block Hessenberg Reduction Using Panel Approach
• Luring Conditions and Their Proof of Necessity through Mathematical Modelling
• Efficient Recommendation for Smart TV Contents
• Materialized View Selection Using Simulated Annealing.