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<strong>Automatic extraction of significant terms from the title and abstract of scientific papers using the machine learning algorithm: A multiple module approach</strong>

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Title Statement <strong>Automatic extraction of significant terms from the title and abstract of scientific papers using the machine learning algorithm: A multiple module approach</strong>
 
Added Entry - Uncontrolled Name Mukherjee, Bhaskar ; Banaras Hindu University
Majhi, Debasis ; Junior Research Fellow, Department of Library & Information Science, Banaras Hindu University, Varanasi
 
Uncontrolled Index Term Library Science; Information Science; Computer Applications
Data mining, Title extraction, Natural Language Processing, YAKE, NLTK, Keyword Extraction-NLP
 
Summary, etc. <p>Keyword extraction is the task of identifying important terms or phrase that are most representative of the sourcedocument. Although the process of automatic extraction of keywords from title is an old method, it was mainly forextraction from a single web document. Our approach differs from previous research works on keyword extraction in severalaspects. For those who are non-expert of the scientific fields, understating scientific research trends is difficult. The purposeof this study is to develop an automatic method of obtaining overviews of a scientific field for non-experts by capturingresearch trends. This empirical study excavates significant term extraction using Natural Language Processing (NLP) tools.More than 15000 titles saved in a .csv file was our dataset and scripts written in Python were our process to compare how farsignificant terms of scientific title corpus are similar or different to the terms available in the abstract of that same scientificarticle corpus. A light-weight unsupervised title extractor, Yet Another Keyword Extractor (YAKE) was used to extract theresults. Based on our analysis, it can be concluded that these algorithms can be used for other fields too by the non-expertsof that subject field to perform automatic extraction of significant words and understanding trends. Our algorithm could be asolution to reduce the labour-intensive manual indexing process.</p>
 
Publication, Distribution, Etc. Annals of Library and Information Studies (ALIS)
2023-04-21 11:08:25
 
Electronic Location and Access http://op.niscair.res.in/index.php/ALIS/article/view/71272
 
Data Source Entry Annals of Library and Information Studies (ALIS); ##issue.vol## 70, ##issue.no## 1 (2023): Annals of Library and Information Studies
 
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