株式会社極東書店トップ ＞ 商品一覧 ＞ Linking and Mining Heterogeneous and Multi-view Data. 2019 ed.
商品詳細
Linking and Mining Heterogeneous and Multi-view Data. 2019 ed.
・ISBN 978-3-030-01871-9 hard EUR 129.99
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| 著者・編者 | P, Deepak / Jurek-Loughrey, Anna (eds.), |
|---|---|
| シリーズ | (Unsupervised and Semi-Supervised Learning) |
| 出版社 | (Springer Nature Switzerland AG, SZ) |
| 出版年月 | 2019 |
| ページ数 | 343 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A02-98708＞ |
解説
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.