Results 31 to 40 of about 177,864 (288)
ALICE:A Pre-trained Language Representation Model for Chinese Technological Text Analysis [PDF]
Jisuanji gongcheng, 2020 The deep model of natural language processing rely on huge,high-quality and human-annotated dataset.In order to alleviate such dependency,this paper proposes a BERT-based natural language processing pre-trained model for Chinese technological text named ...
WANG Yingjie, XIE Bin, LI Ningbo
doaj +1 more source
Combining Overall and Target Oriented Sentiment Analysis over Portuguese Text from Social Media [PDF]
, 2015 This document describes an approach to perform sentiment analysis on social media Portuguese content. In a single system, we perform polarity classification for both the overall sentiment, and target oriented sentiment.
Oliveira, Eduardo +3 more
core +1 more source
BMC Bioinformatics, 2022 Background Automatic and accurate recognition of various biomedical named entities from literature is an important task of biomedical text mining, which is the foundation of extracting biomedical knowledge from unstructured texts into structured formats.
Xiangwen Zheng +5 more
semanticscholar +1 more source
Multiobjective Optimization for Biomedical Named Entity Recognition and Classification
Procedia Technology, 2012 AbstractNamed Entity Recognition and Classification (NERC) is one of the most fundamental and important tasks in biomedical informa–tion extraction. Biomedical named entities (NEs) include mentions of proteins, genes, DNA, RNA etc. which, in general, have complex structures and are difficult to recognize.
Ekbal, Asif +2 more
openaire +1 more source
International Workshop on Semantic Evaluation, 2022 This paper presents a solution for the SemEval-2022 Task 11 Multilingual Complex Named Entity Recognition. What is challenging in this task is detecting semantically ambiguous and complex entities in short and low-context settings.
Keyu Pu +5 more
semanticscholar +1 more source
ParsBERT: Transformer-based Model for Persian Language Understanding
, 2020 The surge of pre-trained language models has begun a new era in the field of Natural Language Processing (NLP) by allowing us to build powerful language models.
Farahani, Marzieh +3 more
core +1 more source
Unsupervised Named-Entity Recognition: Generating Gazetteers and Resolving Ambiguity [PDF]
, 2006 In this paper, we propose a named-entity recognition (NER) system that addresses two major limitations frequently discussed in the field. First, the system requires no human intervention such as manually labeling training data or creating gazetteers ...
Matwin, Stan +2 more
core +2 more sources
HMM based Korean Named Entity Recognition [PDF]
Journal of Systemics, Cybernetics and Informatics, 2003 In this paper, we present a named entity recognition model for Korean Language. Named entity recognition is an essential and important process of Question Answering and Information Extraction system.
Yi-Gyu Hwang +2 more
doaj
Spanish named entity recognition in the biomedical domain [PDF]
, 2018 Named Entity Recognition in the clinical domain and in languages different from English has the difficulty of the absence of complete dictionaries, the informality of texts, the polysemy of terms, the lack of accordance in the boundaries of an entity ...
Cotik, Viviana +2 more
core +1 more source
Media Monitoring and Information Extraction for the Highly Inflected Agglutinative Language Hungarian [PDF]
, 2014 The Europe Media Monitor (EMM) is a fully-automatic system that analyses written online news by gathering articles in over 70 languages and by applying text analysis software for currently 21 languages, without using linguistic tools such as parsers ...
BUCCI Stefano +7 more
core +2 more sources