Topic Modeling Of Small Sequential Documents: Proposed Experiments For Detecting Terror Attacks

Keywords

computer aided analysis; machine learning; national security

Abstract

Research is proposed for improving the human-interpretability of topic models; specifically, for topic models of small sequential documents. Experiments are proposed for evaluating the usefulness of topic modeling. The proposed experiments will model the topics of a diverse set of social media content and attempt to correlate the presence of topics related to terror attacks with actual attacks; additionally, correlations between terror attacks and other topics will be checked for.

Publication Date

11-15-2016

Publication Title

IEEE International Conference on Intelligence and Security Informatics: Cybersecurity and Big Data, ISI 2016

Number of Pages

310-312

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/ISI.2016.7745497

Socpus ID

85003914587 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85003914587

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