Ontology based Approach for Event Detection in Twitter datastreams

被引：2

作者：

Kaushik, R. ^{[1
]}

Chandra, Apoorva S. ^{[1
]}

Mallya, Dilip ^{[1
]}

Chaitanya, J. N. V. K. ^{[1
]}

Kamath, Sowmya S. ^{[1
]}

机构：

[1] Natl Inst Technol Karnataka, Dept Informat Technol, Srinivas Nagar PO, Mangalore 575025, India

来源：

2015 IEEE REGION 10 SYMPOSIUM (TENSYMP) | 2015年

关键词：

Social Media Analysis; Ontology; Event detection; Semantics; Knowledge discovery;

D O I：

10.1109/TENSYMP.2015.19

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, we present a system that attempts to interpret relations in social media data based on automatically constructed dataset-specific ontology. Twitter data pertaining to the real world events such as the launch of products and the buzz generated by it, among the users of Twitter for developing a prototype of the system. Twitter data is filtered using certain tag-words which are used to build an ontology, based on extracted entities. Wikipedia data on the entities are collected and processed semantically to retrieve inherent relations and properties. The system uses these results to discover related entities and the relationships between them. We present the results of experiments to show how the system was able to effectively construct the ontology and discover inherent relationships between the entities belonging to two different datasets.

引用

页码：74 / 77

页数：4

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