Discovering Characteristic Expressions from Literary Works: a New Text Analysis Method beyond N-Gram Statistics and KWIC

Takeda, Masayuki; Matsumoto, Tetsuya; Fukada, Tomoko; Nanri, Ichiro

doi:10.1007/3-540-44418-1_10

Cited by 3 publications

(1 citation statement)

References 7 publications

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“…Categories of keyword and the notion of the distance among multiple categories trees and keyword across were used in a forest model. Work by Takeda et al [12] outline characteristic expression in literary work. Their problem is, take literary work as positive examples (first writer) and negative examples of works by another writer especially in Japanese Poems (Waka poems and prose texts).…”

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confidence: 99%

Profiling and Identifying Individual Users by Their Command Line Usage and Writing Style

Darusalam

Ashman²

2018

Kno. Eng. Da. Sc.

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Profiling and identifying individual users is an approach for intrusion detection in a computer system. User profiles are important in many applications since they record highly user-specific information - profiles are basically built to record information about users or for users to share experiences with each other. This research extends previous research on re-authenticating users with their user profiles. This research focuses on the potential to add psychometric user characteristics into the user model so as to be able to detect unauthorized users who may be masquerading as a genuine user. There are five participants involved in the investigation for formal language user identification. Additionally, we analyze the natural language of two famous writers, Jane Austen & William Shakespeare, in their written works to determine if the same principles can be applied to natural language use. This research used the n-gram analysis method for characterizing user’s style, and can potentially provide accurate user identification. As a result, n-gram analysis of a user's typed inputs offers another method for intrusion detection as it may be able to both positively and negatively identify users. The contribution of this research is to assess the use of a user’s writing styles in both formal language and natural language as a user profile characteristic that could enable intrusion detection where intruders masquerade as real users.

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confidence: 99%