ahmed aliwy | University of Kufa - Iraq (original) (raw)
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Named Entity Recognition (NER) is considered as a task of Information Extraction (IE) which is ef... more Named Entity Recognition (NER) is considered as a task of Information Extraction (IE) which is effective for improving the efficiency of a variety of Natural Language Processing (NLP) tasks, including Relation Extraction (RE), Question Answering (QA), Information Retrieval (IR), etc.NER tries to identify and classify named entities from a specified text, like persons, locations, and organizations, etc. Many researchers have discussed this problem through a variety of approaches, including rule-based and machine learning-based approaches. In recent years, many NER approaches that are based on deep learning have been proposed and improved to obtain precise results .In this paper, a survey of deep learning approaches for NER was presented. Also, the datasets and the evaluation metrics used in each approach were demonstrated. Then, a discussion was provided about the surveyed articles in terms of deep learning NER approaches together with the datasets and evaluation metrics used with ea...
Named Entity Recognition (NER) is considered as a task of Information Extraction (IE) which is ef... more Named Entity Recognition (NER) is considered as a task of Information Extraction (IE) which is effective for improving the efficiency of a variety of Natural Language Processing (NLP) tasks, including Relation Extraction (RE), Question Answering (QA), Information Retrieval (IR), etc.NER tries to identify and classify named entities from a specified text, like persons, locations, and organizations, etc. Many researchers have discussed this problem through a variety of approaches, including rule-based and machine learning-based approaches. In recent years, many NER approaches that are based on deep learning have been proposed and improved to obtain precise results .In this paper, a survey of deep learning approaches for NER was presented. Also, the datasets and the evaluation metrics used in each approach were demonstrated. Then, a discussion was provided about the surveyed articles in terms of deep learning NER approaches together with the datasets and evaluation metrics used with ea...