A Positive-Unlabeled Learning Model for Extending a Vietnamese Petroleum Dictionary Based on Vietnamese Wikipedia Data

Vu, Ngoc Trinh and Nguyen, Quoc Dat and Nguyen, Tien Dat and Nguyen, Manh Cuong and Vu, Van Vuong and Ha, Quang Thuy (2018) A Positive-Unlabeled Learning Model for Extending a Vietnamese Petroleum Dictionary Based on Vietnamese Wikipedia Data. In: ACIIDS 2018: Intelligent Information and Database Systems. Springer Nature 2018, pp. 190-199.

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Abstract

This study provides a positive-unlabeled learning model for extending a Vietnamese petroleum dictionary based on Vietnamese Wikipedia data. Machine learning algorithms with positive and unlabeled data together with separated and combined between Google similarity distance and Cosine similarity distance, used in this study. The data sources used to integrate are English - Vietnamese oil and gas dictionary and the Vietnamese Wikipedia. In the results, a novelty way for data integration with higher accuracy by using a combination of algorithms. The first Vietnamese oil and gas ontology was built in Vietnam. This ontology is a useful tool for staff in the oil and gas industry in training, research, search daily.

Item Type:	Book Section
Subjects:	Information Technology (IT)
Divisions:	Faculty of Information Technology (FIT)
Depositing User:	Hà Quang Thụy
Date Deposited:	07 Apr 2018 01:08
Last Modified:	07 Apr 2018 01:08
URI:	http://eprints.uet.vnu.edu.vn/eprints/id/eprint/2939

Available Versions of this Item

• A Positive-Unlabeled Learning Model for Extending a Vietnamese Petroleum Dictionary Based on Vietnamese Wikipedia Data. (deposited 07 Apr 2018 01:08) [Currently Displayed]
  • A Positive-Unlabeled Learning Model for Extending a Vietnamese Petroleum Dictionary Based on Vietnamese Wikipedia Data. (deposited 18 Apr 2018 03:37)

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