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Time Expression and Named Entity Recognition

Time Expression and Named Entity Recognition


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About the Book

Chapter 1. Introduction.- Chapter 2. Literature Review.- Chapter 3. Data Analysis.- Chapter 4. SynTime: Token Types and Heuristic Rules.- 5. TOMN: Constituent-based Tagging Scheme.- Chapter 6. UGTO: Uncommon Words and Proper Nouns.- Chapter 7. Conclusion and Future Work.
About the Author:

Xiaoshi Zhong received his bachelor degree in computer science from Beihang University (BUAA), China, and his doctoral degree in computer science from Nanyang Technological University (NTU), Singapore. After a short period as a research fellow in NTU, he will join Beijing Institute of Technology (BIT), China, as an Assistant Professor in the School of Computer Science and Technology. His research interests mainly include data analytics, computational linguistics, and natural language processing.

Erik Cambria is the Founder of SenticNet, a Singapore-based company offering B2B sentiment analysis services, and an Associate Professor at NTU, where he also holds the appointment of Provost Chair in Computer Science and Engineering. Prior to joining NTU, he worked at Microsoft Research Asia and HP Labs India and earned his PhD through a joint programme between the University of Stirling and MIT Media Lab. Erik is recipient of many awards, e.g., the 2018 AI's 10 to Watch and the 2019 IEEE Outstanding Early Career award, and is often featured in the news, e.g., Forbes. He is Associate Editor of several journals, e.g., NEUCOM, INFFUS, KBS, IEEE CIM and IEEE Intelligent Systems (where he manages the Department of Affective Computing and Sentiment Analysis), and is involved in many international conferences as PC member, program chair, and speaker.



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Product Details
  • ISBN-13: 9783030789602
  • Publisher: Springer International Publishing
  • Publisher Imprint: Springer
  • Height: 234 mm
  • No of Pages: 96
  • Series Title: Socio-Affective Computing
  • Weight: 394 gr
  • ISBN-10: 3030789608
  • Publisher Date: 28 Aug 2021
  • Binding: Hardback
  • Language: English
  • Returnable: Y
  • Spine Width: 8 mm
  • Width: 156 mm


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