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NLPExplorer: Exploring the Universe of NLP Papers
Understanding the current research trends, problems, and their innovative solutions remains a bottleneck due to the ever-increasing volume of scientific articles. In this paper, we propose NLPExplorer, a completely automatic portal for indexing, searching, and visualizing Natural Language Processing...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7148103/ http://dx.doi.org/10.1007/978-3-030-45442-5_61 |
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author | Parmar, Monarch Jain, Naman Jain, Pranjali Jayakrishna Sahit, P. Pachpande, Soham Singh, Shruti Singh, Mayank |
author_facet | Parmar, Monarch Jain, Naman Jain, Pranjali Jayakrishna Sahit, P. Pachpande, Soham Singh, Shruti Singh, Mayank |
author_sort | Parmar, Monarch |
collection | PubMed |
description | Understanding the current research trends, problems, and their innovative solutions remains a bottleneck due to the ever-increasing volume of scientific articles. In this paper, we propose NLPExplorer, a completely automatic portal for indexing, searching, and visualizing Natural Language Processing (NLP) research volume. NLPExplorer presents interesting insights from papers, authors, venues, and topics. In contrast to previous topic modelling based approaches, we manually curate five course-grained non-exclusive topical categories namely Linguistic Target (Syntax, Discourse, etc.), Tasks (Tagging, Summarization, etc.), Approaches (unsupervised, supervised, etc.), Languages (English, Chinese, etc.) and Dataset types (news, clinical notes, etc.). Some of the novel features include a list of young popular authors, popular URLs and datasets, list of topically diverse papers and recent popular papers. Also, it provides temporal statistics such as yearwise popularity of topics, datasets, and seminal papers. To facilitate future research and system development, we make all the processed dataset accessible through API calls. The current system is available at http://nlpexplorer.org. |
format | Online Article Text |
id | pubmed-7148103 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-71481032020-04-13 NLPExplorer: Exploring the Universe of NLP Papers Parmar, Monarch Jain, Naman Jain, Pranjali Jayakrishna Sahit, P. Pachpande, Soham Singh, Shruti Singh, Mayank Advances in Information Retrieval Article Understanding the current research trends, problems, and their innovative solutions remains a bottleneck due to the ever-increasing volume of scientific articles. In this paper, we propose NLPExplorer, a completely automatic portal for indexing, searching, and visualizing Natural Language Processing (NLP) research volume. NLPExplorer presents interesting insights from papers, authors, venues, and topics. In contrast to previous topic modelling based approaches, we manually curate five course-grained non-exclusive topical categories namely Linguistic Target (Syntax, Discourse, etc.), Tasks (Tagging, Summarization, etc.), Approaches (unsupervised, supervised, etc.), Languages (English, Chinese, etc.) and Dataset types (news, clinical notes, etc.). Some of the novel features include a list of young popular authors, popular URLs and datasets, list of topically diverse papers and recent popular papers. Also, it provides temporal statistics such as yearwise popularity of topics, datasets, and seminal papers. To facilitate future research and system development, we make all the processed dataset accessible through API calls. The current system is available at http://nlpexplorer.org. 2020-03-24 /pmc/articles/PMC7148103/ http://dx.doi.org/10.1007/978-3-030-45442-5_61 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Parmar, Monarch Jain, Naman Jain, Pranjali Jayakrishna Sahit, P. Pachpande, Soham Singh, Shruti Singh, Mayank NLPExplorer: Exploring the Universe of NLP Papers |
title | NLPExplorer: Exploring the Universe of NLP Papers |
title_full | NLPExplorer: Exploring the Universe of NLP Papers |
title_fullStr | NLPExplorer: Exploring the Universe of NLP Papers |
title_full_unstemmed | NLPExplorer: Exploring the Universe of NLP Papers |
title_short | NLPExplorer: Exploring the Universe of NLP Papers |
title_sort | nlpexplorer: exploring the universe of nlp papers |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7148103/ http://dx.doi.org/10.1007/978-3-030-45442-5_61 |
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