Email fraud detection by identifying email sender

Savaliya, Bansi R.; Philip, C. George

doi:10.1109/icecds.2017.8389678

Cited by 2 publications

(1 citation statement)

References 6 publications

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“…Preprocessing tasks involve applying natural language processing techniques to treat the texts by eliminating noise that affects the analytical process and formatting the text to perform subsequent processing. Examples of these preprocessing tasks include text cleaning and normalization, removing special characters, numbers, empty or white spaces, stop words, performing case folding, stemming, and lemmatizing, tokenization, and extraction of n-grams as evidenced by the work by Aboluwarin et al [62], Chandra et al [63], Gil et al [64], Martín et al [47], and Savaliya and Philip [65].…”

Section: Text Mining Techniques and Technologies Applied In Public Se...mentioning

confidence: 99%

Enabling Public Security Text-Based Analytics: A Survey to Outline Research Directions

De Carvalho,

Dos Santos,

Nepomuceno

et al. 2024

Preprint

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Text mining is a technological trend often highlighted in the continuous exchange of information through interconnected media. Its applicability goes beyond private organizations, as the public sector also requires it to treat textual information regarding services offered. Within this scenario, public security emerges as a prominent user of text mining that seeks to ensure the construction of data and knowledgebases to support decision-making about law enforcement actions to ensure citizen welfare. The primary objectives of this article are: (i) to develop a survey to identify text mining applications, techniques, opportunities, and challenges in public security, and (ii) to outline research directions concerning these topics and provide insights so that interested researchers can develop new studies. The literature was searched within four databases: Scopus, IEEE Xplore, ACM Digital Library, and Web of Science. A filtering process was applied to extract the works most aligned with the target theme, resulting in the selection of 194 of the most relevant works for a literature review. There were identified nineteen key applications of text mining related to public security and the most recurrent techniques and technologies reported between 2014 to 2021, supporting outlining three axes for future directions: one with possible expansion of objectives for new research; another on changes and adaptations in scopes for the methodological context; and the last one on expansions and changes in application scenarios based on the literature.

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