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Multidisciplinary Information Retrieval

Overview of attention for book
Cover of 'Multidisciplinary Information Retrieval'

Table of Contents

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    Book Overview
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    Chapter 1 Multilingual and Cross-Lingual News Analysis in the Europe Media Monitor (EMM) (Extended Abstract)
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    Chapter 2 Multidisciplinary Information Retrieval
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    Chapter 3 A Machine Learning Approach for Subjectivity Classification Based on Positional and Discourse Features
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    Chapter 4 Recall-Oriented Evaluation for Information Retrieval Systems
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    Chapter 5 Using ‘Search Transitions’ to Study Searchers’ Investment of Effort: Experiences with Client and Server Side Logging
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    Chapter 6 An IR-Inspired Approach to Recovering Named Entity Tags in Broadcast News
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    Chapter 7 An Exploratory Study on Content-Based Filtering of Call for Papers
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    Chapter 8 Domain Adaptation of General Natural Language Processing Tools for a Patent Claim Visualization System
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    Chapter 9 Concept Extraction from Patent Images Based on Recursive Hybrid Classification
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    Chapter 10 Towards a Framework for Human (Manual) Information Retrieval
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    Chapter 11 A Generalized Framework for Integrated Professional Search Systems
Attention for Chapter 6: An IR-Inspired Approach to Recovering Named Entity Tags in Broadcast News
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4 Mendeley
Summary
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Chapter title
An IR-Inspired Approach to Recovering Named Entity Tags in Broadcast News
Chapter number 6
Book title
Multidisciplinary Information Retrieval
Published by
Springer Berlin Heidelberg, January 2013
DOI 10.1007/978-3-642-41057-4_6
Book ISBNs
978-3-64-241056-7, 978-3-64-241057-4, 978-3-64-241056-7, 978-3-64-241057-4
Authors

Niraj Shrestha, Ivan Vulić, Marie-Francine Moens

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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 %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 25%
Researcher 1 25%
Lecturer 1 25%
Unknown 1 25%
Readers by discipline Count As %
Computer Science 2 50%
Unknown 2 50%

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