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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 The CLSA Model: A Novel Framework for Concept-Level Sentiment Analysis
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    Chapter 2 Building Large Arabic Multi-domain Resources for Sentiment Analysis
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    Chapter 3 Learning Ranked Sentiment Lexicons
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    Chapter 4 Modelling Public Sentiment in Twitter: Using Linguistic Patterns to Enhance Supervised Learning
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    Chapter 5 Trending Sentiment-Topic Detection on Twitter
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    Chapter 6 EmoTwitter – A Fine-Grained Visualization System for Identifying Enduring Sentiments in Tweets
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    Chapter 7 Feature Selection for Twitter Sentiment Analysis: An Experimental Study
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    Chapter 8 An Iterative Emotion Classification Approach for Microblogs
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    Chapter 9 Aspect-Based Sentiment Analysis Using Tree Kernel Based Relation Extraction
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    Chapter 10 Text Integrity Assessment: Sentiment Profile vs Rhetoric Structure
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    Chapter 11 Sentiment Classification with Graph Sparsity Regularization
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    Chapter 12 Detecting Emotion Stimuli in Emotion-Bearing Sentences
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    Chapter 13 Sentiment-Bearing New Words Mining: Exploiting Emoticons and Latent Polarities
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    Chapter 14 Identifying Temporal Information and Tracking Sentiment in Cancer Patients’ Interviews
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    Chapter 15 Using Stylometric Features for Sentiment Classification
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    Chapter 16 Automated Linguistic Personalization of Targeted Marketing Messages Mining User-Generated Text on Social Media
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    Chapter 17 Inferring Aspect-Specific Opinion Structure in Product Reviews Using Co-training
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    Chapter 18 Summarizing Customer Reviews through Aspects and Contexts
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    Chapter 19 An Approach for Intention Mining of Complex Comparative Opinion Why Type Questions Asked on Product Review Sites
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    Chapter 20 TRUPI: Twitter Recommendation Based on Users’ Personal Interests
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    Chapter 21 Computational Linguistics and Intelligent Text Processing
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    Chapter 22 Content-Based Recommender System Enriched with Wordnet Synsets
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    Chapter 23 Active Learning Based Weak Supervision for Textual Survey Response Classification
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    Chapter 24 Detecting and Disambiguating Locations Mentioned in Twitter Messages
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    Chapter 25 Satisfying Poetry Properties Using Constraint Handling Rules
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    Chapter 26 A Multi-strategy Approach for Lexicalizing Linked Open Data
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    Chapter 27 A Dialogue System for Telugu, a Resource-Poor Language
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    Chapter 28 Anti-Summaries: Enhancing Graph-Based Techniques for Summary Extraction with Sentiment Polarity
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    Chapter 29 A Two-Level Keyphrase Extraction Approach
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    Chapter 30 Conceptual Search for Arabic Web Content
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    Chapter 31 Experiments with Query Expansion for Entity Finding
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    Chapter 32 Mixed Language Arabic-English Information Retrieval
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    Chapter 33 Improving Cross Language Information Retrieval Using Corpus Based Query Suggestion Approach
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    Chapter 34 Search Personalization via Aggregation of Multidimensional Evidence About User Interests
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    Chapter 35 Question Analysis for a Closed Domain Question Answering System
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    Chapter 36 Information Extraction with Active Learning: A Case Study in Legal Text
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    Chapter 37 Term Network Approach for Transductive Classification
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    Chapter 38 Calculation of Textual Similarity Using Semantic Relatedness Functions
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    Chapter 39 Confidence Measure for Czech Document Classification
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    Chapter 40 An Approach to Tweets Categorization by Using Machine Learning Classifiers in Oil Business
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    Chapter 41 Long-Distance Continuous Space Language Modeling for Speech Recognition
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    Chapter 42 A Supervised Phrase Selection Strategy for Phonetically Balanced Standard Yorùbá Corpus
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    Chapter 43 Semantic Role Labeling of Speech Transcripts
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    Chapter 44 Latent Topic Model Based Representations for a Robust Theme Identification of Highly Imperfect Automatic Transcriptions
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    Chapter 45 Probabilistic Approach for Detection of Vocal Pathologies in the Arabic Speech
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    Chapter 46 Clustering Relevant Terms and Identifying Types of Statements in Clinical Records
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    Chapter 47 Medical Entities Tagging Using Distant Learning
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    Chapter 48 Identification of Original Document by Using Textual Similarities
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    Chapter 49 Kalema: Digitizing Arabic Content for Accessibility Purposes Using Crowdsourcing
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    Chapter 50 An Enhanced Technique for Offline Arabic Handwritten Words Segmentation
  52. Altmetric Badge
    Chapter 51 Erratum: Aspect-Based Sentiment Analysis Using Tree Kernel Based Relation Extraction
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 (83rd percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

twitter
3 X users
patent
2 patents
wikipedia
1 Wikipedia page

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
76 Mendeley
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Title
Computational Linguistics and Intelligent Text Processing
Published by
Lecture notes in computer science, January 2015
DOI 10.1007/978-3-319-18117-2
ISBNs
978-3-31-918116-5, 978-3-31-918117-2
Editors

Alexander Gelbukh

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 76 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 14%
Student > Bachelor 7 9%
Student > Master 6 8%
Professor 5 7%
Student > Doctoral Student 4 5%
Other 13 17%
Unknown 30 39%
Readers by discipline Count As %
Computer Science 33 43%
Linguistics 5 7%
Mathematics 1 1%
Business, Management and Accounting 1 1%
Nursing and Health Professions 1 1%
Other 1 1%
Unknown 34 45%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 19 December 2018.
All research outputs
#4,137,634
of 22,856,968 outputs
Outputs from Lecture notes in computer science
#964
of 8,127 outputs
Outputs of similar age
#58,209
of 353,273 outputs
Outputs of similar age from Lecture notes in computer science
#60
of 257 outputs
Altmetric has tracked 22,856,968 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,127 research outputs from this source. They receive a mean Attention Score of 5.0. This one has done well, scoring higher than 88% 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 353,273 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 83% of its contemporaries.
We're also able to compare this research output to 257 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.