An ant colony optimisation-based framework for the detection of suspicious content and profile from text corpus
by Asha Kumari; Balkishan
International Journal of Intelligent Systems Technologies and Applications (IJISTA), Vol. 20, No. 1, 2021

Abstract: The technical advancements in the field of short message communication have swiftly raised the human communication means along with the menace of suspiciousness. There is the need to control this peril expanding in the form of suspicious content. Suspicious content can be related to any uninvited message that can lead to rumours, fake news, spam, malicious, and threatening activities. This research work addresses the problem of suspicious content and profile identification from SMS and Twitter microblogs. A framework based on ant colony optimisation is presented for the detection of suspicious content and profile (ACODSCP). Here, the global optimisation attribute of ant colony optimisation (ACO) concept incorporates to determine the suspicious activities effectively with the minimal feature set. In this study, one twitter microblog based text dataset and two SMS based text corpora are utilised. The evaluated results illustrate the promising results of the proposed concept in comparison with existing concepts.

Online publication date: Thu, 29-Apr-2021

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