Linking and Mining Heterogeneous and Multi-view Data

✍ Scribed by Deepak P, Anna Jurek-Loughrey

• Publisher: Springer International Publishing
• Year: 2019
• Tongue: English
• Leaves: 345
• Series: Unsupervised and Semi-Supervised Learning
• Edition: 1st ed.
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter ....Pages i-viii
Multi-View Data Completion (Sahely Bhadra)....Pages 1-25
Multi-View Clustering (Deepak P, Anna Jurek-Loughrey)....Pages 27-53
Semi-supervised and Unsupervised Approaches to Record Pairs Classification in Multi-Source Data Linkage (Anna Jurek-Loughrey, Deepak P)....Pages 55-78
A Review of Unsupervised and Semi-supervised Blocking Methods for Record Linkage (Kevin O’Hare, Anna Jurek-Loughrey, Cassio de Campos)....Pages 79-105
Traffic Sensing and Assessing in Digital Transportation Systems (Hana Rabbouch, Foued Saâdaoui, Rafaa Mraihi)....Pages 107-135
How Did the Discussion Go: Discourse Act Classification in Social Media Conversations (Subhabrata Dutta, Tanmoy Chakraborty, Dipankar Das)....Pages 137-160
Learning from Imbalanced Datasets with Cross-View Cooperation-Based Ensemble Methods (Cécile Capponi, Sokol Koço)....Pages 161-182
Entity Linking in Enterprise Search: Combining Textual and Structural Information (Sumit Bhatia)....Pages 183-199
Clustering Multi-View Data Using Non-negative Matrix Factorization and Manifold Learning for Effective Understanding: A Survey Paper (Khanh Luong, Richi Nayak)....Pages 201-227
Leveraging Heterogeneous Data for Fake News Detection (K. Anoop, Manjary P. Gangan, Deepak P, V. L. Lajish)....Pages 229-264
General Framework for Multi-View Metric Learning (Riikka Huusari, Hachem Kadri, Cécile Capponi)....Pages 265-294
On the Evaluation of Community Detection Algorithms on Heterogeneous Social Media Data (Antonela Tommasel, Daniela Godoy)....Pages 295-333
Back Matter ....Pages 335-343

✦ Subjects

Engineering; Communications Engineering, Networks; Signal, Image and Speech Processing; Pattern Recognition; Data Mining and Knowledge Discovery