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Evaluation of Natural Language and Speech Tools for Italian

Overview of attention for book
Cover of 'Evaluation of Natural Language and Speech Tools for Italian'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 The EVALITA Dependency Parsing Task: From 2007 to 2011
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    Chapter 2 Use of Semantic Information in a Syntactic Dependency Parser
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    Chapter 3 Parsit at Evalita 2011 Dependency Parsing Task
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    Chapter 4 An Ensemble Model for the EVALITA 2011 Dependency Parsing Task
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    Chapter 5 Tuning DeSR for Dependency Parsing of Italian
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    Chapter 6 Looking Back to the EVALITA Constituency Parsing Task: 2007-2011
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    Chapter 7 Domain Adaptation for Dependency Parsing at Evalita 2011
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    Chapter 8 Experiments in Newswire-to-Law Adaptation of Graph-Based Dependency Parsers
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    Chapter 9 Domain Adaptation by Active Learning
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    Chapter 10 Named Entity Recognition on Transcribed Broadcast News at EVALITA 2011
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    Chapter 11 A Simple Yet Effective Approach for Named Entity Recognition from Transcribed Broadcast News
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    Chapter 12 A Combination of Classifiers for Named Entity Recognition on Transcription
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    Chapter 13 The Tanl Tagger for Named Entity Recognition on Transcribed Broadcast News at Evalita 2011
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    Chapter 14 The News People Search Task at EVALITA 2011: Evaluating Cross-Document Coreference Resolution of Named Person Entities in Italian News
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    Chapter 15 Exploiting Background Knowledge for Clustering Person Names
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    Chapter 16 Evalita 2011: Anaphora Resolution Task
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    Chapter 17 UNIPI Participation in the Evalita 2011 Anaphora Resolution Task
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    Chapter 18 Description and Results of the SuperSense Tagging Task
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    Chapter 19 Super-Sense Tagging Using Support Vector Machines and Distributional Features
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    Chapter 20 SuperSense Tagging with a Maximum Entropy Markov Model
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    Chapter 21 EvalIta 2011: The Frame Labelingover Italian Texts Task
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    Chapter 22 Two Level Approach to SRL
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    Chapter 23 Generative and Discriminative Learning in Semantic Role Labeling for Italian
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    Chapter 24 Structured Kernel-Based Learning for the Frame Labeling over Italian Texts
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    Chapter 25 The Lemmatisation Task at the EVALITA 2011 Evaluation Campaign
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    Chapter 26 Italian Lemmatization by Rules with Getaruns
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    Chapter 27 Data Driven Lemmatization and Parsing of Italian
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    Chapter 28 The Tanl Lemmatizer Enriched with a Sequence of Cascading Filters
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    Chapter 29 The AnIta-Lemmatiser: A Tool for Accurate Lemmatisation of Italian Texts
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    Chapter 30 Evalita 2011: Automatic Speech Recognition Large Vocabulary Transcription
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    Chapter 31 The Vocapia Research ASR Systems for Evalita 2011
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    Chapter 32 The FBK ASR System for Evalita 2011
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    Chapter 33 EVALITA 2011: Forced Alignment Task
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    Chapter 34 The SPPAS Participation to the Forced-Alignment Task of Evalita 2011
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    Chapter 35 SAD-Based Italian Forced Alignment Strategies
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    Chapter 36 UNINA System for the EVALITA 2011 Forced Alignment Task
Overall attention for this book and its chapters
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Title
Evaluation of Natural Language and Speech Tools for Italian
Published by
Lecture notes in computer science, January 2013
DOI 10.1007/978-3-642-35828-9
ISBNs
978-3-64-235827-2, 978-3-64-235828-9
Authors

Magnini, Bernardo, Cutugno, Francesco, Falcone, Mauro, Pianta, Emanuele

Editors

Bernardo Magnini, Francesco Cutugno, Mauro Falcone, Emanuele Pianta

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 25%
Unknown 3 75%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 50%
Student > Bachelor 1 25%
Researcher 1 25%
Readers by discipline Count As %
Linguistics 2 50%
Computer Science 2 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 25 January 2017.
All research outputs
#13,854,864
of 22,965,074 outputs
Outputs from Lecture notes in computer science
#4,145
of 8,137 outputs
Outputs of similar age
#163,443
of 281,982 outputs
Outputs of similar age from Lecture notes in computer science
#159
of 315 outputs
Altmetric has tracked 22,965,074 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,137 research outputs from this source. They receive a mean Attention Score of 5.0. This one is in the 47th percentile – i.e., 47% of its peers scored the same or lower than it.
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We're also able to compare this research output to 315 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.