JOURNAL ARTICLE

Domain-specific keyphrase extraction and near-duplicate article detection based on ontology

Abstract

The significant increase in number of the online newspapers has given web users a giant information source. The users are really difficult to manage content as well as check the correctness of articles. In this paper, we introduce algorithms of extracting keyphrase and matching signatures for near-duplicate articles detection. Based on ontology, keyphrases of articles are extracted automatically and similarity of two articles is calculated by using extracted keyphrases. Algorithms are applied on Vietnamese online newspapers for Labor & Employment. Experimental results show that our proposed methods are effective.

Keywords:
Computer science Correctness Information retrieval Domain (mathematical analysis) Newspaper Similarity (geometry) Ontology Matching (statistics) Natural language processing Artificial intelligence Image (mathematics) Algorithm

Metrics

4
Cited By
0.31
FWCI (Field Weighted Citation Impact)
24
Refs
0.79
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Text Analysis Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Web Data Mining and Analysis
Physical Sciences →  Computer Science →  Information Systems
Semantic Web and Ontologies
Physical Sciences →  Computer Science →  Artificial Intelligence

Related Documents

JOURNAL ARTICLE

Automatic Domain-specific Term Extraction in Administrative-domain Ontology

DI Du-FengBaisong Liu

Journal:   Shuju fenxi yu zhishi faxian Year: 2010 Vol: 26 (4)Pages: 59-65
BOOK-CHAPTER

DIKEA: Domain-Independent Keyphrase Extraction Algorithm

David X. WangXiaoying GaoPeter Andreae

Lecture notes in computer science Year: 2012 Pages: 719-730
© 2026 ScienceGate Book Chapters — All rights reserved.