Results 341 to 350 of about 379,251 (377)

Named Entity Recognition

2012
This chapter presents the application of ETL to language independent named entity recognition (NER). The NER task consists of finding all proper nouns in a text and classifying them among several given categories of interest. We apply ETL and ETL Committee to three different corpora in three different languages: Portuguese, Spanish and Dutch.
Ruy Luiz Milidiú, Cicero Nogueira dos Santos   +1 more
openaire   +2 more sources

LSTM Recurrent Neural Networks for Cybersecurity Named Entity Recognition

arXiv.org
The automated and timely conversion of cybersecurity information from unstructured online sources, such as blogs and articles to more formal representations has become a necessity for many applications in the domain nowadays.
Houssem Gasmi, Abdelaziz Bouras
semanticscholar   +1 more source

Med-BERT: A Pretraining Framework for Medical Records Named Entity Recognition

IEEE Transactions on Industrial Informatics, 2022
A large amount of data is generated every day with the development of Internet medical care, which is of great significance for the clinical decision support system and medical real-world research.
Ning Liu, Qian Hu, H. Xu, Xing Xu, Mengxin Chen   +4 more
semanticscholar   +1 more source

Named entity recognition for Polish

Poznan Studies in Contemporary Linguistics, 2019
Abstract In this article we discuss the current state-of-the-art for named entity recognition for Polish. We present publicly available resources and open-source tools for named entity recognition. The overview includes various kind of resources, i.e. guidelines, annotated corpora (NKJP, KPWr, CEN, PST) and lexicons (NELexiconS, PNET, Gazetteer).
Michał Marcińczuk, Aleksander Wawer
openaire   +2 more sources

Speech recognition of a named entity

Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005., 2006
A hierarchical language model is newly applied to identify a named entity consisting of multiple word sequences for continuous speech recognition. By redesigning an out-of-vocabulary model of a single word using phonotactic constraints for a named entity, a hierarchical model is composed harmoniously with conventional word and word-class N-grams ...
Hirofumi Yamamoto, Yoshinori Sagisaka, Y. Okimoto, T. Tomita   +3 more
openaire   +2 more sources

Named Entity Recognition

2014
Named entity recognition (NER) is the problem of locating and categorizing important nouns and proper nouns in a text. In this chapter, we review the general state of research on entity recognition, relevant challenges and the current state of the art works on named entity recognition on Semitic languages.
openaire   +2 more sources

An Overview of Named Entity Recognition

2018 International Conference on Asian Language Processing (IALP), 2018
Named Entity Recognition (NER) is essential for some Natural Language Processing (NLP) tasks. Previous researchers gave a survey of NER in statistical machine learning era, however, research on NER has already changed a lot in recent decade. On the one hand, more and more NER systems adopt deep learning, transfer learning, knowledge base and other ...
Xuezhen Yang, Zhijuan Wang, Xiaobing Zhao, Peng Sun   +3 more
openaire   +2 more sources

Named entity recognition for tweets

ACM Transactions on Intelligent Systems and Technology, 2013
Two main challenges of Named Entity Recognition (NER) for tweets are the insufficient information in a tweet and the lack of training data. We propose a novel method consisting of three core elements: (1) normalization of tweets; (2) combination of a K-Nearest Neighbors (KNN) classifier with a linear Conditional Random Fields (CRF) model; and (3 ...
Xiaohua Liu, Shaodian Zhang, Ming Zhou, Furu Wei   +3 more
openaire   +2 more sources

Named-Entity Recognition in Bengali

Post-Proceedings of the 4th and 5th Workshops of the Forum for Information Retrieval Evaluation, 2013
This paper describes two systems for Named Entity Recognition (NER) and performance of two systems has been compared. The first system is a rule-based one whereas the second one is statistical (based on CRF) in nature. The systems vary in some other aspects too, for example, the first system works on untagged data (not even POS tag is done) to identify
Utpal Garain, Arjun Das, Apurbalal Senapati   +2 more
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A Survey on Named Entity Recognition

2020
Natural language processing is an important research direction and research hotspot in the field of artificial intelligence. Named entity recognition is one of the key tasks, which is to identify entities with specific meanings in the text, such as names of people, places, institutions, proper nouns, etc.
Xin Chen, Geng Chen, Yan Wen, Cong Fan, Ming Chen   +4 more
openaire   +1 more source