An experimental comparison of unsupervised keyphrase extraction techniques for extracting significant information from scientific research articles
The automatic extraction of key information from an article that expresses all of the document’s main elements is referred to as keyphrase extraction. The number of scientific research articles each year is growing. Finding a research article on relevant topics or summarizing a particular research a...
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEE
2021
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| Online Access: | http://umpir.ump.edu.my/id/eprint/32693/ http://umpir.ump.edu.my/id/eprint/32693/1/An%20experimental%20comparison%20of%20unsupervised%20keyphrase%20extraction%20techniques%20.pdf |
| _version_ | 1848824087417192448 |
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| author | Sarwar, Talha Mohd Noor, Noorhuzaimi Karimah |
| author_facet | Sarwar, Talha Mohd Noor, Noorhuzaimi Karimah |
| author_sort | Sarwar, Talha |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | The automatic extraction of key information from an article that expresses all of the document’s main elements is referred to as keyphrase extraction. The number of scientific research articles each year is growing. Finding a research article on relevant topics or summarizing a particular research article using important information has become time-consuming by going through the entire article. Therefore, the textual information processing task involves the automatic keyphrase extraction from a document that expresses all of the document’s main elements. This article aims to make an experimental comparison of different unsupervised keyphrase extraction approaches, namely statistical-based, graph-based, and tree-based. The experiment is conducted upon 120 research articles from different subject areas of the computer science. The comparison between different techniques is made by calculating the precision, recall, and Fl-score. The overall performance of the experimental result shows that KP-Miner, a statistical-based technique, outperforms all the other graph-based and tree-based techniques. Among the other techniques, the tree-based technique TeKET performs better after KPMiner. The statistical-based and tree-based approach performs better than the graph-based approach. |
| first_indexed | 2025-11-15T03:07:27Z |
| format | Conference or Workshop Item |
| id | ump-32693 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:07:27Z |
| publishDate | 2021 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-326932021-12-29T02:14:22Z http://umpir.ump.edu.my/id/eprint/32693/ An experimental comparison of unsupervised keyphrase extraction techniques for extracting significant information from scientific research articles Sarwar, Talha Mohd Noor, Noorhuzaimi Karimah QA76 Computer software TK Electrical engineering. Electronics Nuclear engineering The automatic extraction of key information from an article that expresses all of the document’s main elements is referred to as keyphrase extraction. The number of scientific research articles each year is growing. Finding a research article on relevant topics or summarizing a particular research article using important information has become time-consuming by going through the entire article. Therefore, the textual information processing task involves the automatic keyphrase extraction from a document that expresses all of the document’s main elements. This article aims to make an experimental comparison of different unsupervised keyphrase extraction approaches, namely statistical-based, graph-based, and tree-based. The experiment is conducted upon 120 research articles from different subject areas of the computer science. The comparison between different techniques is made by calculating the precision, recall, and Fl-score. The overall performance of the experimental result shows that KP-Miner, a statistical-based technique, outperforms all the other graph-based and tree-based techniques. Among the other techniques, the tree-based technique TeKET performs better after KPMiner. The statistical-based and tree-based approach performs better than the graph-based approach. IEEE 2021-08 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/32693/1/An%20experimental%20comparison%20of%20unsupervised%20keyphrase%20extraction%20techniques%20.pdf Sarwar, Talha and Mohd Noor, Noorhuzaimi Karimah (2021) An experimental comparison of unsupervised keyphrase extraction techniques for extracting significant information from scientific research articles. In: 7th International Conference on Software Engineering and Computer Systems and 4th International Conference on Computational Science and Information Management, ICSECS-ICOCSIM 2021 , 24 - 26 August 2021 , Pekan, Online. 130 -135.. ISBN 9781665414074 (Published) https://doi.org/10.1109/ICSECS52883.2021.00031 |
| spellingShingle | QA76 Computer software TK Electrical engineering. Electronics Nuclear engineering Sarwar, Talha Mohd Noor, Noorhuzaimi Karimah An experimental comparison of unsupervised keyphrase extraction techniques for extracting significant information from scientific research articles |
| title | An experimental comparison of unsupervised keyphrase extraction techniques for extracting significant information from scientific research articles |
| title_full | An experimental comparison of unsupervised keyphrase extraction techniques for extracting significant information from scientific research articles |
| title_fullStr | An experimental comparison of unsupervised keyphrase extraction techniques for extracting significant information from scientific research articles |
| title_full_unstemmed | An experimental comparison of unsupervised keyphrase extraction techniques for extracting significant information from scientific research articles |
| title_short | An experimental comparison of unsupervised keyphrase extraction techniques for extracting significant information from scientific research articles |
| title_sort | experimental comparison of unsupervised keyphrase extraction techniques for extracting significant information from scientific research articles |
| topic | QA76 Computer software TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/32693/ http://umpir.ump.edu.my/id/eprint/32693/ http://umpir.ump.edu.my/id/eprint/32693/1/An%20experimental%20comparison%20of%20unsupervised%20keyphrase%20extraction%20techniques%20.pdf |