Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts
Latent Structure Models for Natural Language Processing (P19-4)
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| Challenge: | Latent structure models are a powerful tool for compositional data modeling and pipelines. |
| Approach: | This tutorial will cover recent advances in discrete latent structure models . it will discuss their motivation, potential, and limitations . |
| Outcome: | This tutorial will cover recent advances in discrete latent structure models . it will discuss their motivation, potential, and limitations . |
Graph-Based Meaning Representations: Design and Processing (P19-4)
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| Challenge: | This tutorial focuses on representing and processing sentence meaning in the form of labeled directed graphs. |
| Approach: | This tutorial will briefly review relevant background in formal and linguistic semantics . it will also briefly define a unified abstract view on different flavors of semantic graphs - and associated terminology . |
| Outcome: | The tutorial will briefly review relevant background in formal and linguistic semantics . |
Discourse Analysis and Its Applications (P19-4)
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| Challenge: | Discourse processing is a suite of NLP tasks to uncover linguistic structures from texts at several levels, which can support many downstream applications. |
| Approach: | They present a set of tasks to uncover linguistic structures from texts at several levels, which can support many downstream applications. |
| Outcome: | The tutorial covers the basic concepts of discourse analysis and linguistic structures in monologue vs. conversation, synchronous v. asynchronous conversation, and key linguistic structure in discourse analysis. |
Computational Analysis of Political Texts: Bridging Research Efforts Across Communities (P19-4)
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| Challenge: | Political scientists have developed and adopted natural language processing (NLP) methods to exploit text as an additional source of data in their analyses. |
| Approach: | This tutorial aims to provide a gentle introduction to methods and tasks related to computational analysis of political texts from both communities. |
| Outcome: | The main goal of this tutorial is to bring the two research communities closer to each other and contribute to faster and more significant developments in this interdisciplinary area. |
Wikipedia as a Resource for Text Analysis and Retrieval (P19-4)
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| Challenge: | Tutorial examines the role of Wikipedia in tasks related to text analysis and retrieval. |
| Approach: | tutorial examines the role of Wikipedia in tasks related to text analysis and retrieval. |
| Outcome: | This tutorial examines the role of Wikipedia in tasks related to text analysis and retrieval. |
Deep Bayesian Natural Language Processing (P19-4)
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| Challenge: | Introduction to deep Bayesian learning for natural language addresses the fundamentals of statistical models and neural networks. |
| Approach: | This tutorial addresses the advances in deep Bayesian learning for natural language . it focuses on advanced Bayessian models and deep models . authors present case studies and domain applications to tackle different issues . |
| Outcome: | This tutorial focuses on advanced Bayesian models and deep models for natural language . case studies and domain applications are presented to tackle different issues in deep Bayessian processing, learning and understanding. |
Unsupervised Cross-Lingual Representation Learning (P19-4)
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| Challenge: | a comprehensive survey of cutting-edge weakly-supervised and unsupervised cross-lingual word representations is presented . |
| Approach: | This tutorial provides a comprehensive survey of recent work on weakly-supervised and unsupervised cross-lingual word representations. |
| Outcome: | This tutorial provides a comprehensive survey of cutting-edge weakly-supervised and unsupervised word representations. |
Advances in Argument Mining (P19-4)
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| Challenge: | Argument mining is a rapidly growing area of research and research that has seen significant growth over the past few years. |
| Approach: | Argument mining is a new area of research that uses opinion mining to extract opinions . the 6th ACL workshop on argument mining will be in Florence in 2019 . |
| Outcome: | Argument mining is a new area of research and development that has seen significant growth in the past three years. |
Storytelling from Structured Data and Knowledge Graphs : An NLG Perspective (P19-4)
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| Challenge: | tutorial aims to explain the basic concepts of translating structured data into natural language . Various solutions for structured data translation will be discussed . |
| Approach: | tutorial aims to cover foundational, methodological, and system development aspects of translating structured data into natural language . Various solutions starting from traditional rule based/heuristic driven and modern data-driven will be discussed . |
| Outcome: | The tutorial aims to convey challenges and nuances in structured data translation, data representation techniques, and domain adaptable solutions for translation of the data into natural language form. |