Linking and Mining Heterogeneous and Multi-view Data

Autor: Deepak P, Anna Jurek-Loughrey

Jazyk:

Vazba: Pevná

Vydavatel: Springer Nature Switzerland AG

Dostupnost: Skladem u dodavatele

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This book highlights research in linking and mining data from across varied data sources. The author...

Informace o knize

Autor

Deepak P, Anna Jurek-Loughrey

Jazyk

Angličtina

Vazba

Kniha - Pevná

Vydáno

2019

Stránek

343

EAN

9783030018719

Enbook ID

20227344

Vydavatel

Springer Nature Switzerland AG

Hmotnost

694

Rozměry

155 x 235 x 237

Kompletní popis

This book highlights research in linking and mining data from across varied data sources. The authors focus on recent advances in this burgeoning field of multi-source data fusion, with an emphasis on exploratory and unsupervised data analysis, an area of increasing significance with the pace of growth of data vastly outpacing any chance of labeling them manually. The book looks at the underlying algorithms and technologies that facilitate the area within big data analytics, it covers their applications across domains such as smarter transportation, social media, fake news detection and enterprise search among others. This book enables readers to understand a spectrum of advances in this emerging area, and it will hopefully empower them to leverage and develop methods in multi-source data fusion and analytics with applications to a variety of scenarios. Includes advances on unsupervised, semi-supervised and supervised approaches to heterogeneous data linkage and fusion; Covers use cases of analytics over multi-view and heterogeneous data from across a variety of domains such as fake news, smarter transportation and social media, among others; Provides a high-level overview of advances in this emerging field and empowers the reader to explore novel applications and methodologies that would enrich the field.

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Linking and Mining Heterogeneous and Multi-view Data

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