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NLPinAI 2021 : Natural Language Processing in Artificial Intelligence

Online
Event Date: Feb 04, 2021 - Feb 06, 2021
Submission Deadline: Nov 26, 2020
Notification of Acceptance: Dec 14, 2020
Camera Ready Version Due : Dec 22, 2020

Categories

 
NLP

About

Computational and technological developments that incorporate natural language are proliferating. Adequate coverage encounters difficult problems related to partiality, underspecification, and context-dependency, which are signature features of information in nature and natural languages. Furthermore, agents (humans or computational systems) are information conveyors, interpreters, or participate as components of informational content. Generally, language processing depends on agents' knowledge, reasoning, perspectives, and interactions.

The session covers theoretical work, advanced applications, approaches, and techniques for computational models of information and its presentation by language (artificial, human, or natural in other ways). The goal is to promote intelligent natural language processing and related models of thought, mental states, reasoning, and other cognitive processes.

Call For Paper

TOPICS OF INTEREST

We invite contributions relevant to the following topics, without limiting to them:

  • Type Theories for Applications to Language and Information Processing
  • Computational Grammar
  • Computational Syntax
  • Computational Semantics of Natural Languages
  • Computational Syntax-Semantics Interface
  • Interfaces between Morphology, Lexicon, Syntax, Semantics, Speech, Text, Pragmatics
  • Parsing
  • Multilingual Processing
  • Large-Scale Grammars of Natural Languages
  • Models of Computation and Algorithms for Natural Language Processing
  • Computational Models of Partiality, Underspecification, and Context-Dependency
  • Models of Situations, Contexts, and Agents, for Applications to Language Processing
  • Information about Space and Time in Language Models and Processing
  • Models of Computation and Algorithms for Linguistics
  • Data Science in Language Processing
  • Machine Learning of Language
  • Interdisciplinary Methods
  • Integration of formal, Computational, Model Theoretic, Graphical, Diagrammatic, Statistical, and other Related Methods
  • Logic for Information Extraction or Expression in Written and Spoken Language
  • Language Processing Based on Biological Fundamentals of Information and Languages
  • Computational Neuroscience of Language

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