NLPExplorer: exploring the universe of NLP papers

Show simple item record Parmar, Monarch Jain, Naman Jain, Pranjali Sahit, P. Jayakrishna Pachpande, Soham Singh, Shruti Singh, Mayank 2019-11-01T12:49:18Z 2019-11-01T12:49:18Z 2019-10
dc.identifier.citation Parmar, Monarch; Jain, Naman; Jain, Pranjali; Sahit, P. Jayakrishna; Pachpande, Soham; Singh, Shruti and Singh, Mayank, "NLPExplorer: exploring the universe of NLP papers", arXiv, Cornell University Library, DOI: arXiv:1910.07351, Oct. 2019. en_US
dc.description.abstract 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, a 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 datasets accessible through API calls.
dc.description.statementofresponsibility by Monarch Parmar, Naman Jain, Pranjali Jain, P Jayakrishna Sahit, Soham Pachpande, Shruti Singh and Mayank Singh
dc.language.iso en_US en_US
dc.publisher Cornell University Library en_US
dc.title NLPExplorer: exploring the universe of NLP papers en_US
dc.type Preprint en_US

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