A flexible keyphrase extraction technique for academic literature

Gollam, Rabby and Azad, Saiful and Paolo, Casari and Kamal Z., Zamli and Mohammed Mostafizur, Rahman (2018) A flexible keyphrase extraction technique for academic literature. In: 3rd International Conference on Computer Science and Computational Intelligence 2018, 7 - 8 September 2018 , BINUS University @ Alam SuteraTangerang, Indonesia. pp. 553-563., 135. ISSN 18770509 ISBN 9789811087875

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A keyphrase extraction technique endeavors to extract quality keyphrases from a given document, which provide a high-level summary of that document. Except statistical keyphrase extraction approaches, all other approaches are either domain-dependent or require a su�cient amount of training data, which are rare at present. Therefore, in this paper, a new tree-based automatic keyphrase extraction technique is proposed, which is domain-independent and employs nominal statistical knowledge; but no train data are required. The proposed technique extracts a quality keyphrase through forming a tree from a candidate keyphrase; and later, it is expanded or shrunk or remained in the same state depending on other similar candidate keyphrases. At the end, keyphrases are extracted from the resultant trees based on a value, � (which is the Maturity Index (MI) of a node in the tree), which enables flexibility in this process. A small � value would yield many and/or lengthy keyphrases (greedy approach); whereas, a large � value would yield lower and/or abbreviated keyphrases (conservative approach). Thereby, a user can extract his/her desired-level of keyphrases through tuning � value. The e�ectiveness of the proposed technique is evaluated on an actual corpus, and compared with Rapid Automatic Keyphrase Extraction (RAKE) technique.

Item Type: Conference or Workshop Item (Lecture)
Additional Information: Index by Scopus
Uncontrolled Keywords: Candidate keyphrase; Keyphrase; Automatic keyphrase extraction technique; Tree data structure
Subjects: Q Science > QA Mathematics > QA76 Computer software
Faculty/Division: Faculty of Computer System And Software Engineering
Centre of Excellence: IBM Centre of Excellence
Depositing User: Pn. Hazlinda Abd Rahman
Date Deposited: 13 Dec 2018 03:19
Last Modified: 13 Dec 2018 03:19
URI: http://umpir.ump.edu.my/id/eprint/22468
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