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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 Planning the Future of Language Resources: The Role of the FLaReNet Network
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    Chapter 2 Cross-Lingual Alignment of FrameNet Annotations through Hidden Markov Models
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    Chapter 3 On the Automatic Generation of Intermediate Logic Forms for WordNet Glosses
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    Chapter 4 Worth Its Weight in Gold or Yet Another Resource — A Comparative Study of Wiktionary, OpenThesaurus and GermaNet
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    Chapter 5 Issues in Analyzing Telugu Sentences towards Building a Telugu Treebank
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    Chapter 6 EusPropBank: Integrating Semantic Information in the Basque Dependency Treebank
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    Chapter 7 Morphological Annotation of a Corpus with a Collaborative Multiplayer Game
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    Chapter 8 Computational Models of Language Acquisition
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    Chapter 9 ETL Ensembles for Chunking, NER and SRL
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    Chapter 10 Unsupervised Part-of-Speech Disambiguation for High Frequency Words and Its Influence on Unsupervised Parsing
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    Chapter 11 A Machine Learning Parser Using an Unlexicalized Distituent Model
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    Chapter 12 Ontology-Based Semantic Interpretation as Grammar Rule Constraints
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    Chapter 13 Towards a Cascade of Morpho-syntactic Tools for Arabic Natural Language Processing
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    Chapter 14 An Open-Source Computational Grammar for Romanian
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    Chapter 15 Chinese Event Descriptive Clause Splitting with Structured SVMs
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    Chapter 16 An Experimental Study on Unsupervised Graph-based Word Sense Disambiguation
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    Chapter 17 A Case Study of Using Web Search Statistics: Case Restoration
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    Chapter 18 A Named Entity Extraction using Word Information Repeatedly Collected from Unlabeled Data
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    Chapter 19 A Distributional Semantics Approach to Simultaneous Recognition of Multiple Classes of Named Entities
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    Chapter 20 The Recognition and Interpretation of Motion in Language
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    Chapter 21 Flexible Disambiguation in DTS
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    Chapter 22 A Syntactic Textual Entailment System Based on Dependency Parser
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    Chapter 23 Semantic Annotation of Transcribed Audio Broadcast News Using Contextual Features in Graphical Discriminative Models
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    Chapter 24 Lexical Chains Using Distributional Measures of Concept Distance
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    Chapter 25 Incorporating Cohesive Devices into Entity Grid Model in Evaluating Local Coherence of Japanese Text
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    Chapter 26 A Sequential Model for Discourse Segmentation
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    Chapter 27 Towards Automatic Detection and Tracking of Topic Change
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    Chapter 28 Modelling Illocutionary Structure: Combining Empirical Studies with Formal Model Analysis
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    Chapter 29 A Polyphonic Model and System for Inter-animation Analysis in Chat Conversations with Multiple Participants
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    Chapter 30 Computational Models for Incongruity Detection in Humour
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    Chapter 31 Emotions in Words: Developing a Multilingual WordNet-Affect
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    Chapter 32 Emotion Holder for Emotional Verbs – The Role of Subject and Syntax
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    Chapter 33 A Chunk-Driven Bootstrapping Approach to Extracting Translation Patterns
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    Chapter 34 Computing Transfer Score in Example-Based Machine Translation
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    Chapter 35 Systematic Processing of Long Sentences in Rule Based Portuguese-Chinese Machine Translation
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    Chapter 36 Syntax Augmented Inversion Transduction Grammars for Machine Translation
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    Chapter 37 Syntactic Structure Transfer in a Tamil to Hindi MT System – A Hybrid Approach
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    Chapter 38 A Maximum Entropy Approach to Syntactic Translation Rule Filtering
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    Chapter 39 Mining Parenthetical Translations for Polish-English Lexica
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    Chapter 40 Automatic Generation of Bilingual Dictionaries Using Intermediary Languages and Comparable Corpora
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    Chapter 41 Hierarchical Finite-State Models for Speech Translation Using Categorization of Phrases
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    Chapter 42 Drive-by Language Identification
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    Chapter 43 Identification of Translationese: A Machine Learning Approach
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    Chapter 44 Acquiring IE Patterns through Distributional Lexical Semantic Models
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    Chapter 45 Multi-view Bootstrapping for Relation Extraction by Exploring Web Features and Linguistic Features
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    Chapter 46 Sequential Patterns to Discover and Characterise Biological Relations
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    Chapter 47 Extraction of Genic Interactions with the Recursive Logical Theory of an Ontology
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    Chapter 48 Ontological Parsing of Encyclopedia Information
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    Chapter 49 Selecting the N-Top Retrieval Result Lists for an Effective Data Fusion
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    Chapter 50 Multi Word Term Queries for Focused Information Retrieval
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    Chapter 51 Optimal IR: How Far Away?
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    Chapter 52 Adaptive Term Weighting through Stochastic Optimization
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    Chapter 53 Enhancing Text Classification by Information Embedded in the Test Set
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    Chapter 54 Rank Distance Aggregation as a Fixed Classifier Combining Rule for Text Categorization
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    Chapter 55 The Influence of Collocation Segmentation and Top 10 Items to Keyword Assignment Performance
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    Chapter 56 A General Bio-inspired Method to Improve the Short-Text Clustering Task
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    Chapter 57 An Empirical Study on the Feature’s Type Effect on the Automatic Classification of Arabic Documents
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    Chapter 58 Word Length n-Grams for Text Re-use Detection
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    Chapter 59 Who’s the Thief? Automatic Detection of the Direction of Plagiarism
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    Chapter 60 Integer Linear Programming for Dutch Sentence Compression
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    Chapter 61 GEMS: Generative Modeling for Evaluation of Summaries
  63. Altmetric Badge
    Chapter 62 Quantitative Evaluation of Grammaticality of Summaries
  64. Altmetric Badge
    Chapter 63 Integrating Contrast in a Framework for Predicting Prosody
Overall attention for this book and its chapters
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

Mentioned by

twitter
1 X user
wikipedia
5 Wikipedia pages

Citations

dimensions_citation
9 Dimensions

Readers on

mendeley
537 Mendeley
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Title
Computational Linguistics and Intelligent Text Processing
Published by
Lecture notes in computer science, January 2010
DOI 10.1007/978-3-642-12116-6
ISBNs
978-3-64-212115-9, 978-3-64-212116-6
Authors

Alexander Gelbukh

Editors

Alexander Gelbukh

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 537 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 12 2%
Spain 6 1%
United Kingdom 6 1%
Brazil 6 1%
Germany 4 <1%
Italy 3 <1%
Indonesia 2 <1%
France 2 <1%
Turkey 2 <1%
Other 18 3%
Unknown 476 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 131 24%
Student > Master 112 21%
Researcher 59 11%
Student > Bachelor 50 9%
Student > Doctoral Student 28 5%
Other 99 18%
Unknown 58 11%
Readers by discipline Count As %
Computer Science 321 60%
Linguistics 34 6%
Social Sciences 26 5%
Engineering 20 4%
Business, Management and Accounting 16 3%
Other 52 10%
Unknown 68 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 08 June 2022.
All research outputs
#6,954,391
of 22,805,349 outputs
Outputs from Lecture notes in computer science
#2,286
of 8,126 outputs
Outputs of similar age
#45,607
of 163,943 outputs
Outputs of similar age from Lecture notes in computer science
#35
of 189 outputs
Altmetric has tracked 22,805,349 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 8,126 research outputs from this source. They receive a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 70% 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 163,943 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 189 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.