Data Analytics for Social Microblogging Platforms (Paperback)

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Data Analysis for Social Microblogging Platforms explores the nature of microblog datasets, also covering the larger field which focuses on information, data and knowledge in the context of natural language processing. The book investigates a range of significant computational techniques which enable data and computer scientists to recognize patterns in these vast datasets, including machine learning, data mining algorithms, rough set and fuzzy set theory, evolutionary computations, combinatorial pattern matching, clustering, summarization and classification. Chapters focus on basic online micro blogging data analysis research methodologies, community detection, summarization application development, performance evaluation and their applications in big data.

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Product Description

Data Analysis for Social Microblogging Platforms explores the nature of microblog datasets, also covering the larger field which focuses on information, data and knowledge in the context of natural language processing. The book investigates a range of significant computational techniques which enable data and computer scientists to recognize patterns in these vast datasets, including machine learning, data mining algorithms, rough set and fuzzy set theory, evolutionary computations, combinatorial pattern matching, clustering, summarization and classification. Chapters focus on basic online micro blogging data analysis research methodologies, community detection, summarization application development, performance evaluation and their applications in big data.

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Product Details

General

Imprint

Academic Press Inc

Country of origin

United Kingdom

Series

Hybrid Computational Intelligence for Pattern Analysis and Understanding

Release date

November 2022

Availability

Expected to ship within 12 - 17 working days

First published

2023

Authors

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Dimensions

229 x 152mm (L x W)

Format

Paperback

Pages

328

ISBN-13

978-0-323-91785-8

Barcode

9780323917858

Categories

LSN

0-323-91785-2



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