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Computational Linguistics and Intelligent Text Processing

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Cover of 'Computational Linguistics and Intelligent Text Processing'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Using Word Association Norms to Measure Corpus Representativeness
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    Chapter 2 Optimality Theory as a Framework for Lexical Acquisition
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    Chapter 3 Verb Clustering for Brazilian Portuguese
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    Chapter 4 Spreading Relation Annotations in a Lexical Semantic Network Applied to Radiology
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    Chapter 5 Issues in Encoding the Writing of Nepal’s Languages
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    Chapter 6 Compound Terms and Their Multi-word Variants: Case of German and Russian Languages
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    Chapter 7 A Fully Automated Approach for Arabic Slang Lexicon Extraction from Microblogs
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    Chapter 8 Simple TF·IDF Is Not the Best You Can Get for Regionalism Classification
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    Chapter 9 Improved Text Extraction from PDF Documents for Large-Scale Natural Language Processing
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    Chapter 10 Computational Linguistics and Intelligent Text Processing
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    Chapter 11 Obtaining Better Word Representations via Language Transfer
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    Chapter 12 Exploring Applications of Representation Learning in Nepali
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    Chapter 13 Topic Models Incorporating Statistical Word Senses
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    Chapter 14 How Preprocessing Affects Unsupervised Keyphrase Extraction
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    Chapter 15 Methods and Algorithms for Unsupervised Learning of Morphology
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    Chapter 16 Morphological Analysis of the Bishnupriya Manipuri Language Using Finite State Transducers
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    Chapter 17 A Hybrid Approach to the Development of Part-of-Speech Tagger for Kafi-noonoo Text
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    Chapter 18 Modified Differential Evolution for Biochemical Name Recognizer
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    Chapter 19 Extended CFG Formalism for Grammar Checker and Parser Development
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    Chapter 20 Dealing with Function Words in Unsupervised Dependency Parsing
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    Chapter 21 When Rules Meet Bigrams
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    Chapter 22 Methodology for Connecting Nouns to Their Modifying Adjectives
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    Chapter 23 Constituency Parsing of Complex Noun Sequences in Hindi
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    Chapter 24 Amharic Sentence Parsing Using Base Phrase Chunking
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    Chapter 25 A Machine Learning Approach to Pronominal Anaphora Resolution in Dialogue Based Intelligent Tutoring Systems
  27. Altmetric Badge
    Chapter 26 A Maximum Entropy Based Honorificity Identification for Bengali Pronominal Anaphora Resolution
  28. Altmetric Badge
    Chapter 27 Computational Linguistics and Intelligent Text Processing
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    Chapter 28 Annotation Game for Textual Entailment Evaluation
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    Chapter 29 Axiomatizing Complex Concepts from Fundamentals
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    Chapter 30 A Semantics Oriented Grammar for Chinese Treebanking
  32. Altmetric Badge
    Chapter 31 Computational Linguistics and Intelligent Text Processing
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    Chapter 32 Sense-Specific Implicative Commitments
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    Chapter 33 A Tiered Approach to the Recognition of Metaphor
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    Chapter 34 Knowledge Discovery with CRF-Based Clustering of Named Entities without a Priori Classes
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    Chapter 35 Semi-supervised SRL System with Bayesian Inference
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    Chapter 36 A Sentence Similarity Method Based on Chunking and Information Content
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    Chapter 37 An Investigation on the Influence of Genres and Textual Organisation on the Use of Discourse Relations
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    Chapter 38 Discourse Tagging for Indian Languages
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    Chapter 39 Classification-Based Referring Expression Generation
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    Chapter 40 Generating Relational Descriptions Involving Mutual Disambiguation
  42. Altmetric Badge
    Chapter 41 Bayesian Inverse Reinforcement Learning for Modeling Conversational Agents in a Virtual Environment
  43. Altmetric Badge
    Chapter 42 Learning to Summarize Time Series Data
Attention for Chapter 25: A Machine Learning Approach to Pronominal Anaphora Resolution in Dialogue Based Intelligent Tutoring Systems
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Chapter title
A Machine Learning Approach to Pronominal Anaphora Resolution in Dialogue Based Intelligent Tutoring Systems
Chapter number 25
Book title
Computational Linguistics and Intelligent Text Processing
Published in
Lecture notes in computer science, April 2014
DOI 10.1007/978-3-642-54906-9_25
Book ISBNs
978-3-64-254905-2, 978-3-64-254906-9
Authors

Nobal B. Niraula, Vasile Rus, Niraula, Nobal B., Rus, Vasile

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 5 26%
Student > Master 5 26%
Lecturer 3 16%
Researcher 2 11%
Other 1 5%
Other 1 5%
Unknown 2 11%
Readers by discipline Count As %
Computer Science 10 53%
Engineering 2 11%
Agricultural and Biological Sciences 1 5%
Psychology 1 5%
Linguistics 1 5%
Other 0 0%
Unknown 4 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 24 April 2014.
All research outputs
#20,265,771
of 22,796,179 outputs
Outputs from Lecture notes in computer science
#6,984
of 8,127 outputs
Outputs of similar age
#193,191
of 226,136 outputs
Outputs of similar age from Lecture notes in computer science
#82
of 92 outputs
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So far Altmetric has tracked 8,127 research outputs from this source. They receive a mean Attention Score of 5.0. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 92 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.