Title :
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
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;
Conference_Titel :
Emerging Technologies (ICET), 2012 International Conference on
Conference_Location :
Islamabad
Print_ISBN :
978-1-4673-4452-4
DOI :
10.1109/ICET.2012.6375469
