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Computational Linguistics and Intelligent Text Processing

Overview of attention for book
Cover of 'Computational Linguistics and Intelligent Text Processing'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Towards a Universal Grammar for Natural Language Processing
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    Chapter 2 Deletions and Node Reconstructions in a Dependency-Based Multilevel Annotation Scheme
  4. Altmetric Badge
    Chapter 3 Enriching, Editing, and Representing Interlinear Glossed Text
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    Chapter 4 Comparing Neural Lexical Models of a Classic National Corpus and a Web Corpus: The Case for Russian
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    Chapter 5 Lexical Network Enrichment Using Association Rules Model
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    Chapter 6 When was Macbeth Written? Mapping Book to Time
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    Chapter 7 Tharawat: A Vision for a Comprehensive Resource for Arabic Computational Processing
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    Chapter 8 High Quality Arabic Lexical Ontology Based on MUHIT, WordNet, SUMO and DBpedia
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    Chapter 9 Building a Nasa Yuwe Language Test Collection
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    Chapter 10 Making Morphologies the “Easy” Way
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    Chapter 11 To Split or Not, and If so, Where? Theoretical and Empirical Aspects of Unsupervised Morphological Segmentation
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    Chapter 12 Data-Driven Morphological Analysis and Disambiguation for Kazakh
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    Chapter 13 Statistical Sandhi Splitter for Agglutinative Languages
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    Chapter 14 Chunking in Turkish with Conditional Random Fields
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    Chapter 15 Statistical Arabic Grammar Analyzer
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    Chapter 16 Bayesian Finite Mixture Models for Probabilistic Context-Free Grammars
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    Chapter 17 Employing Oracle Confusion for Parse Quality Estimation
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    Chapter 18 Experiments on Sentence Boundary Detection in User-Generated Web Content
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    Chapter 19 An Investigation of Neural Embeddings for Coreference Resolution
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    Chapter 20 Feature Selection in Anaphora Resolution for Bengali: A Multiobjective Approach
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    Chapter 21 A Language Modeling Approach for Acronym Expansion Disambiguation
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    Chapter 22 Web Person Disambiguation Using Hierarchical Co-reference Model
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    Chapter 23 From Natural Logic to Natural Reasoning
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    Chapter 24 A Unified Framework to Identify and Extract Uncertainty Cues, Holders, and Scopes in One Fell-Swoop
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    Chapter 25 Lemon and Tea Are Not Similar: Measuring Word-to-Word Similarity by Combining Different Methods
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    Chapter 26 Domain-Specific Semantic Relatedness from Wikipedia Structure: A Case Study in Biomedical Text
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    Chapter 27 Unsupervised Induction of Meaningful Semantic Classes through Selectional Preferences
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    Chapter 28 Hypernym Extraction: Combining Machine-Learning and Dependency Grammar
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    Chapter 29 Arabic Event Detection in Social Media
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    Chapter 30 Learning Semantically Rich Event Inference Rules Using Definition of Verbs
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    Chapter 31 Rehabilitation of Count-Based Models for Word Vector Representations
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    Chapter 32 Word Representations in Vector Space and their Applications for Arabic
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    Chapter 33 Short Text Hashing Improved by Integrating Multi-granularity Topics and Tags
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    Chapter 34 A Computational Approach for Corpus Based Analysis of Reduplicated Words in Bengali
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    Chapter 35 Automatic Dialogue Act Annotation within Arabic Debates
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    Chapter 36 E-Quotes: Enunciative Modalities Analysis Tool for Direct Reported Speech in Arabic
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    Chapter 37 Textual Entailment Using Different Similarity Metrics
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    Chapter 38 Translation Induction on Indian Language Corpora Using Translingual Themes from Other Languages
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    Chapter 39 English-Arabic Statistical Machine Translation: State of the Art
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    Chapter 40 Mining Parallel Resources for Machine Translation from Comparable Corpora
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    Chapter 41 Statistical Machine Translation from and into Morphologically Rich and Low Resourced Languages
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    Chapter 42 Adaptive Tuning for Statistical Machine Translation (AdapT)
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    Chapter 43 A Hybrid Approach for Word Alignment with Statistical Modeling and Chunker
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    Chapter 44 Improving Bilingual Search Performance Using Compact Full-Text Indices
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    Chapter 45 Neutralizing the Effect of Translation Shifts on Automatic Machine Translation Evaluation
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    Chapter 46 Arabic Transliteration of Romanized Tunisian Dialect Text: A Preliminary Investigation
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    Chapter 47 Cross-Dialectal Arabic Processing
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    Chapter 48 Language Set Identification in Noisy Synthetic Multilingual Documents
  50. Altmetric Badge
    Chapter 49 Feature Analysis for Native Language Identification
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

10 tweeters
1 patent
1 Facebook page
1 Wikipedia page

Readers on

80 Mendeley
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Computational Linguistics and Intelligent Text Processing
Published by
Lecture notes in computer science, January 2015
DOI 10.1007/978-3-319-18111-0
978-3-31-918110-3, 978-3-31-918111-0

Alexander Gelbukh

Twitter Demographics

The data shown below were collected from the profiles of 10 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 80 100%

Demographic breakdown

Readers by professional status Count As %
Professor 3 4%
Student > Bachelor 1 1%
Lecturer 1 1%
Unknown 75 94%
Readers by discipline Count As %
Computer Science 4 5%
Psychology 1 1%
Unknown 75 94%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 January 2019.
All research outputs
of 14,557,796 outputs
Outputs from Lecture notes in computer science
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Outputs of similar age
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Outputs of similar age from Lecture notes in computer science
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Altmetric has tracked 14,557,796 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,469 research outputs from this source. They receive a mean Attention Score of 4.5. This one has done particularly well, scoring higher than 94% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 266,687 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 104 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.