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Big Data in Complex Systems

Part of the Studies in Big Data Book Series (volume 9)

Editors: Hassanien, Aboul Ella; Azar, Ahmad Taher; Snasael, Vaclav; Kacprzyk, Janusz; Abawajy, Jemal H.

DOI: 10.1007/978-3-319-11056-1

ISBN: 978-3-319-11055-4

Publisher: Springer International Publishing - Springer Journals

Jan 1, 2015

1 - 10 of 17 Chapters

LitStream

Chapter 1Cloud Computing Infrastructure for Massive Data: A Gigantic Task Ahead

Vashist, Renu

Pages: 1 –28

[Today, in the era of computer we collect and store data from innumerable sources and some of these are Internet transactions, social media, mobile devices and automated sensors. From all of these sources massive or big data is generated and gathered for finding the useful patterns. The amount of...
LitStream

Chapter 2Big Data Movement: A Challenge in Data Processing

Pokorný, Jaroslav; Škoda, Petr; Zelinka, Ivan; Bednárek, David; Zavoral, Filip; Kruliš, Martin; Šaloun, Petr

Pages: 29 –69

[This chapter discusses modern methods of data processing, especially data parallelization and data processing by bio-inspired methods. The synthesis of novel methods is performed by selected evolutionary algorithms and demonstrated on the astrophysical data sets. Such approach is now...
LitStream

Chapter 3Towards Robust Performance Guarantees for Models Learned from High-Dimensional Data

Henriques, Rui; Madeira, Sara C.

Pages: 71 –104

[Models learned from high-dimensional spaces, where the high number of features can exceed the number of observations, are susceptible to overfit since the selection of subspaces of interest for the learning task is prone to occur by chance. In these spaces, the performance of models is commonly...
LitStream

Chapter 4Stream Clustering Algorithms: A Primer

Kaur, Sharanjit; Bhatnagar, Vasudha; Chakravarthy, Sharma

Pages: 105 –145

[Stream data has become ubiquitous due to advances in acquisition technology and pervades numerous applications. These massive data gathered as continuous flow, are often accompanied by dire need for real-time processing. One aspect of data streams deals with storage management and processing of...
LitStream

Chapter 5Cross Language Duplicate Record Detection in Big Data

Yousef, Ahmed H.

Pages: 147 –171

[The importance of data accuracy and quality has increased with the explosion of data size. This factor is crucial to ensure the success of any cross-enterprise integration applications, business intelligence or data mining solutions. Detecting duplicate data that represent the same real world...
LitStream

Chapter 6A Novel Hybridized Rough Set and Improved Harmony Search Based Feature Selection for Protein Sequence Classification

Bagyamathi, M.; Inbarani, H. Hannah

Pages: 173 –204

[The progress in bio-informatics and biotechnology area has generated a big amount of sequence data that requires a detailed analysis. Recent advances in future generation sequencing technologies have resulted in a tremendous raise in the rate of that protein sequence data are being obtained. Big...
LitStream

Chapter 7Autonomic Discovery of News Evolvement in Twitter

Adedoyin-Olowe, Mariam; Gaber, Mohamed Medhat; Stahl, Frederic; Gomes, João Bártolo

Pages: 205 –229

[Recently the continuous increase in data sizes has resulted in many data processing challenges. This increase has compelled data users to find automatic means of looking into databases to bring out vital information. Retrieving information from ‘Big data’, (as it is often referred to) can be...
LitStream

Chapter 8Hybrid Tolerance Rough Set Based Intelligent Approaches for Social Tagging Systems

Inbarani, H. Hannah; Kumar, S. Selva

Pages: 231 –261

[The major challenge with Big Data analysis is the generation of huge amounts of data over a short period like Social tagging system. Social Tagging systems such as BibSonomy and del.icio.us have become progressively popular with the widespread use of the internet. The social tagging system is a...
LitStream

Chapter 9Exploitation of Healthcare Databases in Anesthesiology and Surgical Care for Comparing Comorbidity Indexes in Cholecystectomized Patients

Béjar-Prado, Luís; Gili-Ortiz, Enrique; López-Méndez, Julio

Pages: 263 –292

[Objective: Charlson comorbidity index (CCI) and Elixhauser comorbidity index (ECI) have been used as prognostic tools in surgical and medical research. We compared their ability to predict in-hospital mortality among cholecystectomized patients using a Spanish large database of 87 hospitals...
LitStream

Chapter 10Sickness Absence and Record Linkage Using Primary Healthcare, Hospital and Occupational Databases

Gili-Miner, Miguel; Cabanillas-Moruno, Juan Luís; Ramírez-Ramírez, Gloria

Pages: 293 –322

[Objective: Charlson comorbidity index (CCI) has been adapted to primary care (PC) patients to determine chronic illness costs. We retrospectively evaluated its ability to predict sickness absence, hospital admissions and in-hospital mortality among 1,826,190 workers followed during the period...

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