Research on the similarity between nodes with hypernymy-hyponymy relations based on IC and taxonomical structure
Joint Authors
Source
The International Arab Journal of Information Technology
Issue
Vol. 19, Issue 3 (31 May. 2022), pp.388-395, 8 p.
Publisher
Zarqa University Deanship of Scientific Research
Publication Date
2022-05-31
Country of Publication
Jordan
No. of Pages
8
Main Subjects
Information Technology and Computer Science
Abstract EN
The similarity method has an important effect on some tasks of natural language processing, such as information retrieval, automatic translation and named entity recognition.
Hypernymy/hyponymy relations are widespread in semantic webs and knowledge graphs, so computing the similarity of hypernymy/hyponymy is a key issue in the text processing field.
All measures of both feature-based and IC-based methods have obvious deficiencies.
The feature-based method estimated the similarity by the depth of the node, and the IC-based method computed the similarity by the position of the deepest common parent.
The deficiency of the feature-based method and IC-based method is that they include one parameter, so the performance is slightly inaccurate and unstable.
To address this deficiency, our paper proposed a hybrid method that computes the similarity of hypernymy/hyponymy by a hybrid parameter (dhype(lch)) that implies two parameters: depth of the node and position of the deepest common parent.
Compared with several similarity methods, the proposed method achieved better performance in terms of accuracy rate, Pearson correlation coefficient and artificial fitting effect.
American Psychological Association (APA)
Zhang, Xiaogang& Sun, Lili. 2022. Research on the similarity between nodes with hypernymy-hyponymy relations based on IC and taxonomical structure. The International Arab Journal of Information Technology،Vol. 19, no. 3, pp.388-395.
https://search.emarefa.net/detail/BIM-1437361
Modern Language Association (MLA)
Zhang, Xiaogang& Sun, Lili. Research on the similarity between nodes with hypernymy-hyponymy relations based on IC and taxonomical structure. The International Arab Journal of Information Technology Vol. 19, no. 3 (May. 2022), pp.388-395.
https://search.emarefa.net/detail/BIM-1437361
American Medical Association (AMA)
Zhang, Xiaogang& Sun, Lili. Research on the similarity between nodes with hypernymy-hyponymy relations based on IC and taxonomical structure. The International Arab Journal of Information Technology. 2022. Vol. 19, no. 3, pp.388-395.
https://search.emarefa.net/detail/BIM-1437361
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 394-395
Record ID
BIM-1437361