Scalable Information Systems: 5th International Conference, INFOSCALE 2014, Seoul, South Korea, September 25-26, 2014, Revised Selected Papers

Scalable Information Systems: 5th International Conference, INFOSCALE 2014, Seoul, South Korea, September 25-26, 2014, Revised Selected Papers

Scalable Information Systems: 5th International Conference, INFOSCALE 2014, Seoul, South Korea, September 25-26, 2014, Revised Selected Papers

Scalable Information Systems: 5th International Conference, INFOSCALE 2014, Seoul, South Korea, September 25-26, 2014, Revised Selected Papers

eBook2015 (2015)

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Overview

This book constitutes the thoroughly refereed post-conference proceedings of the International Conference on Scalable Information Systems, INFOSCALE 2014, held in September 2014 in Seoul, South Korea. The 9 revised full papers presented were carefully reviewed and selected from 14 submissions. The papers cover a wide range of topics such as scalable data analysis and big data applications.

Product Details

ISBN-13: 9783319168685
Publisher: Springer-Verlag New York, LLC
Publication date: 04/06/2015
Series: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering , #139
Sold by: Barnes & Noble
Format: eBook
File size: 2 MB

Table of Contents

Scalable Similarity Search for Big Data - Challenges and Research Objectives.- Content-based analytics of Diffusion on Social Big Data: a Case Study on Korean Telecommunication Companies.- Multi-modal Similarity Retrieval with a Shared Distributed Data Store.- An Efficient Approach for Complex Data Summarization.- A Novel Approach for Network Traffic Summarization.- Heart Disease Diagnosis Using Co-Clustering.- An Investigation of Scalable Anomaly Detection Techniques for a Large Network of Wi-Fi Hotspots.- Link Scheduling for Data Collection in Multichannel Wireless Sensor Networks A Design of Sensor Data Ontology for a Large Scale Crop Growth Environment System.- Real-Time Data Flow Language Processing System for Handling Streams of Data.

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