Negation and Speculation Detection

Noa P. Cruz Díaz | University of Huelva
Manuel J. Maña López | University of Huelva
ISBN 9789027202178 | EUR 95.00 | USD 143.00
ISBN 9789027202161 | EUR 33.00 | USD 49.95
ISBN 9789027262950 | EUR 95.00/33.00*
| USD 143.00/49.95*
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Negation and speculation detection is an emerging topic that has attracted the attention of many researchers, and there is clearly a lack of relevant textbooks and survey texts. This book aims to define negation and speculation from a natural language processing perspective, to explain the need for processing these phenomena, to summarise existing research on processing negation and speculation, to provide a list of resources and tools, and to speculate about future developments in this research area. An advantage of this book is that it will not only provide an overview of the state of the art in negation and speculation detection, but will also introduce newly developed data sets and scripts. It will be useful for students of natural language processing subjects who are interested in understanding this task in more depth and for researchers with an interest in these phenomena in order to improve performance in other natural language processing tasks.
[Natural Language Processing, 13] 2019.  ix, 95 pp.
Publishing status: Available
Table of Contents
“Overall, the book is structured in a logical and clear manner and is written in precise and concise academic language. The fact that the volume under review is not ‘bulky’ (i.e. only ninety-five pages in length) does not detract from its value. Readers would feel like sitting vis-a`-vis with the authors while reading the book, and therefore it could be used as either a classroom text or a supplement reading. Nevertheless, the book may require readers to have basic statistics knowledge and data analytic techniques. Particularly, it may appeal to those who specialize in quantitative linguistics, computational linguistics, NLP, corpus linguistics, corpus-based translation studies, and so forth. Those who attempt to employ quantitative approaches to investigate negative and speculative language in other domains would also find this book useful. For these reasons, Cruz Díaz and Maña López’s present work is a great contribution to the field of quantitative studies and is well worth recommending.”
Cited by

Cited by 6 other publications

Jiménez-Zafra, Salud María, Noa P. Cruz-Díaz, Maite Taboada & María Teresa Martín-Valdivia
2021. Negation detection for sentiment analysis: A case study in Spanish. Natural Language Engineering 27:2  pp. 225 ff. DOI logo
Narayanan, Sankaran, Pradeep Achan, P Venkat Rangan & Sreeranga P. Rajan
2021. Unified concept and assertion detection using contextual multi-task learning in a clinical decision support system. Journal of Biomedical Informatics 122  pp. 103898 ff. DOI logo
Ofek, Nir
2023. Sentiment Analysis for Social Text. In Machine Learning for Data Science Handbook,  pp. 801 ff. DOI logo
Solarte Pabón, Oswaldo, Orlando Montenegro, Maria Torrente, Alejandro Rodríguez González, Mariano Provencio & Ernestina Menasalvas
2022. Negation and uncertainty detection in clinical texts written in Spanish: a deep learning-based approach. PeerJ Computer Science 8  pp. e913 ff. DOI logo
Solarte Pabón, Oswaldo, Maria Torrente, Mariano Provencio, Alejandro Rodríguez-Gonzalez & Ernestina Menasalvas
2021. Integrating Speculation Detection and Deep Learning to Extract Lung Cancer Diagnosis from Clinical Notes. Applied Sciences 11:2  pp. 865 ff. DOI logo
Solarte-Pabón, Oswaldo, Ernestina Menasalvas & Alejandro Rodriguez-González
2020. Spa-neg: An Approach for Negation Detection in Clinical Text Written in Spanish. In Bioinformatics and Biomedical Engineering [Lecture Notes in Computer Science, 12108],  pp. 323 ff. DOI logo

This list is based on CrossRef data as of 16 september 2023. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.


Main BIC Subject

CF: Linguistics

Main BISAC Subject

LAN009000: LANGUAGE ARTS & DISCIPLINES / Linguistics / General
ONIX Metadata
ONIX 2.1
ONIX 3.0
U.S. Library of Congress Control Number:  2018047742 | Marc record