Author Identification is one of the application of text mining and is the task of investigating author of the anonymous text document. Application of author Identification includes in digital forensic, plagiarism detection, copyright issues, etc. The numerous amount of work is already done on English language perhaps Author identification of Indian regional languages is limited. This research paper presents Author identification on Indian regional Marathi Language. In this paper proposing a technique for identifying probabilistic authors via linguistic stylometry i.e. the statistical analysis of variations in literary style between one author or genre with another. In total 11 features are extracted with 8 lexical and syntactic features and 3 word N-gram features. Experimentation is performed with 8 features and machine learning algorithms, i.e. k-nearest neighbor, Naïve Bayes and Support Vector Machine. Moreover, result based on word n-gram i.e. unigram, bigram and trigram are also presented. Experimentation result shows better result with word N-gram method.

Author Identification, Text Mining, Machine Learning, Marathi Language, Stylometry

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