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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 Damping Sentiment Analysis in Online Communication: Discussions, Monologs and Dialogs
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    Chapter 2 Optimal Feature Selection for Sentiment Analysis
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    Chapter 3 Measuring the Effect of Discourse Structure on Sentiment Analysis
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    Chapter 4 Lost in Translation: Viability of Machine Translation for Cross Language Sentiment Analysis
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    Chapter 5 An Enhanced Semantic Tree Kernel for Sentiment Polarity Classification
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    Chapter 6 Combining Supervised and Unsupervised Polarity Classification for non-English Reviews
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    Chapter 7 Word Polarity Detection Using a Multilingual Approach
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    Chapter 8 Mining Automatic Speech Transcripts for the Retrieval of Problematic Calls
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    Chapter 9 Cross-Lingual Projections vs. Corpora Extracted Subjectivity Lexicons for Less-Resourced Languages
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    Chapter 10 Predicting Subjectivity Orientation of Online Forum Threads
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    Chapter 11 Distant Supervision for Emotion Classification with Discrete Binary Values
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    Chapter 12 Using Google n-Grams to Expand Word-Emotion Association Lexicon
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    Chapter 13 A Joint Prediction Model for Multiple Emotions Analysis in Sentences
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    Chapter 14 Evaluating the impact of syntax and semantics on emotion recognition from text
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    Chapter 15 Chinese Emotion Lexicon Developing via Multi-lingual Lexical Resources Integration
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    Chapter 16 N-Gram-Based Recognition of Threatening Tweets
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    Chapter 17 Distinguishing the Popularity between Topics: A System for Up-to-Date Opinion Retrieval and Mining in the Web
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    Chapter 18 No Free Lunch in Factored Phrase-Based Machine Translation
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    Chapter 19 Domain Adaptation in Statistical Machine Translation Using Comparable Corpora: Case Study for English Latvian IT Localisation
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    Chapter 20 Assessing the Accuracy of Discourse Connective Translations: Validation of an Automatic Metric
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    Chapter 21 An Empirical Study on Word Segmentation for Chinese Machine Translation
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    Chapter 22 Class-Based Language Models for Chinese-English Parallel Corpus
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    Chapter 23 Building a Bilingual Dictionary from a Japanese-Chinese Patent Corpus
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    Chapter 24 A Diagnostic Evaluation Approach for English to Hindi MT Using Linguistic Checkpoints and Error Rates
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    Chapter 25 Leveraging Arabic-English Bilingual Corpora with Crowd Sourcing-Based Annotation for Arabic-Hebrew SMT
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    Chapter 26 Automatic and Human Evaluation on English-Croatian Legislative Test Set
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    Chapter 27 Enhancing Search: Events and Their Discourse Context
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    Chapter 28 Distributional Term Representations for Short-Text Categorization
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    Chapter 29 Learning Bayesian Network Using Parse Trees for Extraction of Protein-Protein Interaction
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    Chapter 30 A Model for Information Extraction in Portuguese Based on Text Patterns
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    Chapter 31 A Study on Query Expansion Based on Topic Distributions of Retrieved Documents
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    Chapter 32 Link Analysis for Representing and Retrieving Legal Information
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    Chapter 33 Discursive Sentence Compression
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    Chapter 34 A Knowledge Induced Graph-Theoretical Model for Extract and Abstract Single Document Summarization
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    Chapter 35 Hierarchical Clustering in Improving Microblog Stream Summarization
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    Chapter 36 Summary Evaluation: Together We Stand NPowER-ed
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    Chapter 37 Explanation in Computational Stylometry
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    Chapter 38 The Use of Orthogonal Similarity Relations in the Prediction of Authorship
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    Chapter 39 ERNESTA: A Sentence Simplification Tool for Children’s Stories in Italian
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    Chapter 40 Automatic Text Simplification in Spanish: A Comparative Evaluation of Complementing Modules
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    Chapter 41 The Impact of Lexical Simplification by Verbal Paraphrases for People with and without Dyslexia
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    Chapter 42 Detecting Apposition for Text Simplification in Basque
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    Chapter 43 Automation of Linguistic Creativ itas for Ads logia
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    Chapter 44 Allongos: Longitudinal Alignment for the Genetic Study of Writers’ Drafts
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    Chapter 45 A Combined Method Based on Stochastic and Linguistic Paradigm for the Understanding of Arabic Spontaneous Utterances
  47. Altmetric Badge
    Chapter 46 Evidence in Automatic Error Correction Improves Learners’ English Skill
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 (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

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5 X users
wikipedia
1 Wikipedia page

Readers on

mendeley
19 Mendeley
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Title
Computational Linguistics and Intelligent Text Processing
Published by
Lecture notes in computer science, January 2013
DOI 10.1007/978-3-642-37256-8
ISBNs
978-3-64-237255-1, 978-3-64-237256-8
Authors

Alexander Gelbukh

Editors

Gelbukh, Alexander

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 21%
Student > Bachelor 2 11%
Professor > Associate Professor 2 11%
Student > Master 1 5%
Researcher 1 5%
Other 1 5%
Unknown 8 42%
Readers by discipline Count As %
Computer Science 5 26%
Business, Management and Accounting 1 5%
Linguistics 1 5%
Arts and Humanities 1 5%
Agricultural and Biological Sciences 1 5%
Other 3 16%
Unknown 7 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 27 November 2013.
All research outputs
#4,558,868
of 22,805,349 outputs
Outputs from Lecture notes in computer science
#1,501
of 8,126 outputs
Outputs of similar age
#49,114
of 281,105 outputs
Outputs of similar age from Lecture notes in computer science
#59
of 314 outputs
Altmetric has tracked 22,805,349 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,126 research outputs from this source. They receive a mean Attention Score of 5.0. This one has done well, scoring higher than 81% 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 281,105 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 82% of its contemporaries.
We're also able to compare this research output to 314 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.