Computational Linguistics and Intelligent Text Processing - Info and Reading Options
16th International Conference, CICLing 2015, Cairo, Egypt, April 14-20, 2015, Proceedings, Part I
By Alexander Gelbukh
"Computational Linguistics and Intelligent Text Processing" was published by Springer in 2015 - Cham, it has 662 pages and the language of the book is English.
“Computational Linguistics and Intelligent Text Processing” Metadata:
- Title: ➤ Computational Linguistics and Intelligent Text Processing
- Author: Alexander Gelbukh
- Language: English
- Number of Pages: 662
- Publisher: Springer
- Publish Date: 2015
- Publish Location: Cham
- Library of Congress Classification: QA76.9.N38P98-98.5QA
“Computational Linguistics and Intelligent Text Processing” Subjects and Themes:
- Subjects: ➤ Data Mining and Knowledge Discovery - Database management - Information storage and retrieval systems - Information organization - Computer science - Information retrieval - Information Systems Applications (incl. Internet) - Artificial Intelligence (incl. Robotics) - Data mining - Artificial intelligence - Computational linguistics - Natural language processing (computer science) - Text processing (computer science) - Computational intelligence - Discourse analysis - Comparative linguistics - Long Now Manual for Civilization
Edition Specifications:
- Weight: 10.292
Edition Identifiers:
- The Open Library ID: OL34385089M - OL19836244W
- ISBN-13: 9783319181103 - 9783319181110
- All ISBNs: 9783319181103 - 9783319181110
AI-generated Review of “Computational Linguistics and Intelligent Text Processing”:
"Computational Linguistics and Intelligent Text Processing" Description:
Open Data:
Intro -- Preface -- Organization -- Contents - Part I -- Grammar Formalismsand Lexical Resources -- Towards a Universal Grammar for Natural Language Processing -- 1 Introduction -- 2 Motivation -- 3 Design Principles -- 4 Word Segmentation -- 5 Morphological Annotation -- 6 Syntactic Annotation -- 7 Conclusion -- References -- Deletions and Node Reconstructions in a Dependency-Based Multilevel Annotation Scheme -- 1 Motivation and Specification of Deletions (Ellipsis) -- 2 Treatment of Ellipsis in Some of the Advanced Annotation Schemes for Different Languages -- 3 Ellipsis and Node Reconstruction in the Prague Dependency Treebank -- 3.1 The Prague Dependency Treebank -- 3.2 Deletions in the Representation of the Surface Shape of the Sentence -- 3.3 Reconstructions of Nodes on the Tectogrammatical Level -- 3.4 Some Simple Statistics -- 4 Summary and Outlook -- References -- Enriching, Editing, and Representing Interlinear Glossed Text -- 1 Introduction -- 2 Interlinear Glossed Text -- 2.1 Collecting IGT -- 2.2 Enriching IGT -- 2.3 Using Enriched IGT -- 3 Xigt: An XML Representation of the Enriched IGT -- 3.1 Representing Enriched IGT in Xigt -- 3.2 Processing Documents with the Xigt API -- 4 INTENT: A Package for Creating Enriched IGT -- 4.1 Toolkit Components -- 4.2 Implementation of INTENT -- 5 XigtEdit: A GUI Editor for Enriched IGT -- 5.1 Main Functionality of XigtEdit -- 5.2 Editing Parent Tiers -- 5.3 Implementation of XigtEdit -- 6 Conclusion -- References -- Comparing Neural Lexical Models of a Classic National Corpus and a Web Corpus: The Case for Russian -- 1 Introduction -- 2 Library of Babel vs. Selected Works: The Corpora Used -- 3 Learning Word Embeddings and Choosing Test Sets to Compare -- 4 What's Different: Analysis of Lexical Units' Neighbors in RNC and the Internet Corpus -- 5 Discussion -- 6 Limitations and Future Work
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