Dynamic entity and relationship extraction from news articles

Author

Haq, Mazhar Ul ; Ahmed, Hasnat ; Qamar, Ali Mustafa

Author_Institution

Dept. of Comput., Nat. Univ. of Sci. & Technol. (NUST), Islamabad, Pakistan

fYear

2012

fDate

8-9 Oct. 2012

Firstpage

1

Lastpage

5

Abstract

In structured as well as unstructured data, information extraction (IE) and information retrieval (IR) techniques are gaining popularity in order to produce a realistic output. The Internet users are growing day by day and becoming a popular source for spreading the information through news/blogs etc. To monitor this information, a lot of quality work has been done in that perspective. Related to news monitoring, our proposed unsupervised machine learning approach will fetch the entities and relationships from the news document itself and through comparison with other related news documents, it will form a cluster. We propose, in this paper, a dynamic model for entity extraction and relationship in order to monitor the news reported in the news articles.

Keywords

Web sites; data structures; document handling; information retrieval; unsupervised learning; blogs; dynamic entity extraction; dynamic relationship extraction; information extraction technique; information retrieval technique; news articles; news documents; news monitoring; structured data technique; unstructured data technique; unsupervised machine learning; Assembly; Context; Data mining; Machine learning; Manuals; Monitoring; Tagging; Entity extraction; document grouping; relationship extraction; unsupervised classification;

fLanguage

English

Publisher

ieee

Conference_Titel

Emerging Technologies (ICET), 2012 International Conference on

Conference_Location

Islamabad

Print_ISBN

978-1-4673-4452-4

Type

conf

DOI

10.1109/ICET.2012.6375469

Filename

6375469