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• W2000703448 abstract "The Internet’s numerous benefits have always beencoupled with shortcomings due to the abuses of onlineanonymity. Writeprint identification is a technique to identifyindividuals based on textual identity cues people leave behindonline messages. Character n-gram is one of the most effectiveapproaches to identify writeprint according to previousresearch. In this study, we propose a variable length charactern-gram based writeprint identification framework to addressthe identity tracing problem, integrating a genetic algorithm(GA) based feature selection component to solve the definitionproblem of n. To examine the approach, experiments areconducted on a test bed encompassing hundreds of reviewsposted by 20 Amazon customers. The experimental resultsshow the proposed approach is effective, obtaining aconsiderable improvement in identification accuracy and aheavy reduction of feature dimensionality." @default.
• W2000703448 created "2016-06-24" @default.
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• W2000703448 date "2010-01-01" @default.
• W2000703448 modified "2023-10-17" @default.
• W2000703448 title "Variable Length Character N-Gram Approach for Online Writeprint Identification" @default.
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• W2000703448 doi "https://doi.org/10.1109/mines.2010.109" @default.
• W2000703448 hasPublicationYear "2010" @default.
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