Deepak P is currently a Lecturer (Assistant Professor) in Computer Science at Queen’s University Belfast. His research interests lie across various sub-fields of data analytics such as natural language processing, information retrieval, data mining, machine learning and databases. He has authored more than 50 research papers in top avenues in data analytics, and has ten granted patents from USPTO. Prior to joining Queen’s University in 2015, he was a researcher at IBM Research India for many years. He is a Senior Member of the IEEE and the ACM, and is a recipient of the Indian National Academy of Engineering Young Engineer Award.Anna Jurek-Loughrey is currently a Lecturer (Assistant Professor) in Computer Science at Queen’s University Belfast. Her work has spanned a diverse set of topics in the area of data analytics comprising supervised and unsupervised machine learning, record linkage, sensor-based activity recognition within smart environments, social media analytics with application to health and security. Before joining Queen’s in 2015 she worked as a data scientist at Repknight Ltd for two years.

• Chapter 1. Multi-view Data Completion.- Chapter 2. Multi-view Clustering.- Chapter 3. Semi-supervised and Unsupervised Approaches to Record Pairs Classification in Multi-source Data Linkage.- Chapter 4. A Review of Unsupervised and Semi-Supervised Blocking Methods for Record Linkage.- Chapter 5. Traffic Sensing & Assessing in Digital Transportation Systems.- Chapter 6. How did the discussion go: Discourse act classification in social media conversations.- Chapter 7. Entity Linking in Enterprise Search: Combining Textual and Structural Information.- Chapter 8. Clustering Multi-view Data Using Non-negative Matrix Factorization and Manifold Learning for Effective Understanding: A Survey Paper.- Chapter 9. Leveraging Heterogeneous Data for Fake News Detection.- Chapter 10. On the Evaluation of Community Detection Algorithms on Heterogeneous Social Media Data.- Chapter 11. General Framework for Multi-View Metric Learning.- Chapter 12. Learning from imbalanced datasets with cross-view cooperation-based ensemble methods.

Deepak P is currently a Lecturer (Assistant Professor) in Computer Science at Queen’s University Belfast. His research interests lie across various sub-fields of data analytics such as natural language processing, information retrieval, data mining, machine learning and databases. He has authored more than 50 research papers in top avenues in data analytics, and has ten granted patents from USPTO. Prior to joining Queen’s University in 2015, he was a researcher at IBM Research India for many years. He is a Senior Member of the IEEE and the ACM, and is a recipient of the Indian National Academy of Engineering Young Engineer Award.Anna Jurek-Loughrey is currently a Lecturer (Assistant Professor) in Computer Science at Queen’s University Belfast. Her work has spanned a diverse set of topics in the area of data analytics comprising supervised and unsupervised machine learning, record linkage, sensor-based activity recognition within smart environments, social media analytics with application to health and security. Before joining Queen’s in 2015 she worked as a data scientist at Repknight Ltd for two years.

• Chapter 1. Multi-view Data Completion.- Chapter 2. Multi-view Clustering.- Chapter 3. Semi-supervised and Unsupervised Approaches to Record Pairs Classification in Multi-source Data Linkage.- Chapter 4. A Review of Unsupervised and Semi-Supervised Blocking Methods for Record Linkage.- Chapter 5. Traffic Sensing & Assessing in Digital Transportation Systems.- Chapter 6. How did the discussion go: Discourse act classification in social media conversations.- Chapter 7. Entity Linking in Enterprise Search: Combining Textual and Structural Information.- Chapter 8. Clustering Multi-view Data Using Non-negative Matrix Factorization and Manifold Learning for Effective Understanding: A Survey Paper.- Chapter 9. Leveraging Heterogeneous Data for Fake News Detection.- Chapter 10. On the Evaluation of Community Detection Algorithms on Heterogeneous Social Media Data.- Chapter 11. General Framework for Multi-View Metric Learning.- Chapter 12. Learning from imbalanced datasets with cross-view cooperation-based ensemble methods.

Deepak P is currently a Lecturer (Assistant Professor) in Computer Science at Queen’s University Belfast. His research interests lie across various sub-fields of data analytics such as natural language processing, information retrieval, data mining, machine learning and databases. He has authored more than 50 research papers in top avenues in data analytics, and has ten granted patents from USPTO. Prior to joining Queen’s University in 2015, he was a researcher at IBM Research India for many years. He is a Senior Member of the IEEE and the ACM, and is a recipient of the Indian National Academy of Engineering Young Engineer Award.Anna Jurek-Loughrey is currently a Lecturer (Assistant Professor) in Computer Science at Queen’s University Belfast. Her work has spanned a diverse set of topics in the area of data analytics comprising supervised and unsupervised machine learning, record linkage, sensor-based activity recognition within smart environments, social media analytics with application to health and security. Before joining Queen’s in 2015 she worked as a data scientist at Repknight Ltd for two years.

• Chapter 1. Multi-view Data Completion.- Chapter 2. Multi-view Clustering.- Chapter 3. Semi-supervised and Unsupervised Approaches to Record Pairs Classification in Multi-source Data Linkage.- Chapter 4. A Review of Unsupervised and Semi-Supervised Blocking Methods for Record Linkage.- Chapter 5. Traffic Sensing & Assessing in Digital Transportation Systems.- Chapter 6. How did the discussion go: Discourse act classification in social media conversations.- Chapter 7. Entity Linking in Enterprise Search: Combining Textual and Structural Information.- Chapter 8. Clustering Multi-view Data Using Non-negative Matrix Factorization and Manifold Learning for Effective Understanding: A Survey Paper.- Chapter 9. Leveraging Heterogeneous Data for Fake News Detection.- Chapter 10. On the Evaluation of Community Detection Algorithms on Heterogeneous Social Media Data.- Chapter 11. General Framework for Multi-View Metric Learning.- Chapter 12. Learning from imbalanced datasets with cross-view cooperation-based ensemble methods.