Inference of Fine-grained Attributes of Bengali Corpus for Stylometry Detection



Document title: Inference of Fine-grained Attributes of Bengali Corpus for Stylometry Detection
Journal: Polibits
Database: PERIÓDICA
System number: 000355983
ISSN: 1870-9044
Authors: 1
1
Institutions: 1Jadavpur University, Department of Computer Science and Engineering, Calcuta, Bengala Occidental. India
Year:
Number: 44
Country: México
Language: Inglés
Document type: Artículo
Approach: Aplicado, descriptivo
English abstract Stylometry, the science of inferring characteristics of the author from the characteristics of documents written by that author, is a problem with a long history and belongs to the core task of Text categorization that involves authorship identification, plagiarism detection, forensic investigation, computer security, copyright and estáte disputes etc. In this work, we present a strategy for stylometry detection of documents written in Bengali. We adopt a set of fine–grained attribute features with a set of lexical markers for the analysis of the text and use three semi–supervised measures for making decisions. Finally, a majority voting approach has been taken for final classification. The system is fully automatic and language–independent. Evaluation results of our attempt for Bengali author' s stylometry detection show reasonably promising accuracy in comparison to the baseline model
Disciplines: Ciencias de la computación
Keyword: Inteligencia artificial,
Análisis de textos,
Estilometría,
Marcadores de estilo,
Distancia euclideana
Keyword: Computer science,
Artificial intelligence,
Text analysis,
Stylometry,
Style markers,
Euclidean distance
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