Results 81 to 90 of about 2,702,605 (333)

Attention-Based End-To-End Named Entity Recognition From Speech

, 2021
| openaire: EC/H2020/780069/EU//MeMADNamed entities are heavily used in the field of spoken language understanding, which uses speech as an input. The standard way of doing named entity recognition from speech involves a pipeline of two systems, where ...
Mikko Kurimo, Dejan Porjazovski, Leinonen, Juho, Kurimo, Mikko, Juho Leinonen, Porjazovski, Dejan   +5 more
core   +1 more source

SemEval-2022 Task 11: Multilingual Complex Named Entity Recognition (MultiCoNER)

International Workshop on Semantic Evaluation, 2022
We present the findings of SemEval-2022 Task 11 on Multilingual Complex Named Entity Recognition MULTICONER. Divided into 13 tracks, the task focused on methods to identify complex named entities (like names of movies, products and groups) in 11 ...
S. Malmasi, Anjie Fang, B. Fetahu, Sudipta Kar, Oleg Rokhlenko   +4 more
semanticscholar   +1 more source

Code and Named Entity Recognition in StackOverflow [PDF]

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020
updated with better results. (To appear in ACL 2020)
Jeniya Tabassum, Mounica Maddela, Wei Xu 0004, Alan Ritter   +3 more
openaire   +3 more sources

Classifiers Fusion for Arabic Named Entity Recognition [PDF]

The Egyptian Journal of Language Engineering, 2014
This paper presents a new approach to Arabic Name Entity Recognition (ANER). The introduced approach usesdifferent sets of features that are both language independent and language specific in a discriminative and generative machine learning frameworks ...
Wasim Abdulwasea, Sherif Abdou, Hassanin Barhamtoshy   +2 more
doaj   +1 more source

From junk to function — How weak selection in eukaryotes builds new parts and drives genomic complexity

FEBS Letters, EarlyView.
How do genomes gain new functional parts? In eukaryotes, which tend to evolve under weak selection, much of the genome is junk. Palazzo and Qiu borrow the logic of Markov chains to show how non‐functional DNA becomes functional through the appearance of intermediate states, which arise due to epistasis, buffering, and biochemical messiness, allowing ...
Alexander F. Palazzo, Yi Qiu
wiley   +1 more source

Learning Relatedness Measures for Entity Linking [PDF]

, 2013
Entity Linking is the task of detecting, in text documents, relevant mentions to entities of a given knowledge base. To this end, entity-linking algorithms use several signals and features extracted from the input text or from the knowl- edge base.
Lucchese, Claudio, Orlando, Salvatore, Salvatore Orlando, Salvatore Trani, Trani, Salvatore, Diego Ceccarelli, Claudio Lucchese, Raffaele Perego, Salvatore Orl, Ceccarelli, Diego, Perego, Raffaele, Diego Ceccarelli, Claudio Lucchese, Salvatore Trani, Salvatore Orlando, Raffaele Perego   +15 more
core   +1 more source

An automatically built named entity lexicon for Arabic [PDF]

, 2010
We have successfully adapted and extended the automatic Multilingual, Interoperable Named Entity Lexicon approach to Arabic, using Arabic WordNet (AWN) and Arabic Wikipedia (AWK).
Attia, Mohammed, Monachini, Monica, Toral, Antonio, Tounsi, Lamia, van Genabith, Josef   +4 more
core   +2 more sources

Cross-Lingual Named Entity Recognition Based on Attention and Adversarial Training

Applied Sciences, 2023
Named entity recognition aims to extract entities with specific meaning from unstructured text. Currently, deep learning methods have been widely used for this task and have achieved remarkable results, but it is often difficult to achieve better results
Hao Wang, Lekai Zhou, Jianyong Duan, Li He   +3 more
doaj   +1 more source

Chinese Overlapping Named Entity Recognition Method Based on Label Clustering [PDF]

Jisuanji gongcheng, 2020
To address complex nested relations between named entities and overlapping boundaries of adjacent named entities caused by mislabeling in corpus,this paper proposes a method of Chinese overlapping Named Entity Recognition(NER).First,a hierarchical ...
WEN Xiuxiu, MA Chao, GAO Yuanyuan, KANG Zilu
doaj   +1 more source

Deep learning for named entity recognition in Turkish radiology reports. [PDF]

Diagn Interv Radiol
PURPOSE: The primary objective of this research is to enhance the accuracy and efficiency of information extraction from radiology reports. In addressing this objective, the study aims to develop and evaluate a deep learning framework for named entity ...
Abdullahi AA, Ganiz MC, Koç U, Gökhan MB, Aydın C, Özdemir AB.   +5 more
europepmc   +2 more sources