Document embedding approach for efficient authorship attribution
- Resource Type
- Conference
- Authors
- Agun, Hayri Volkan; Yilmazel, Ozgur
- Source
- 2017 2nd International Conference on Knowledge Engineering and Applications (ICKEA) Knowledge Engineering and Applications (ICKEA), 2017 2nd International Conference on. :194-198 Oct, 2017
- Subject
- Engineering Profession
Training
Text categorization
Adaptation models
Predictive models
Multilayer perceptrons
Context modeling
authorship attribution
document embeddings
bag of words model
text classification
- Language
Authorship attribution has been well studied in terms of text classification with many diverse feature sets. However, finding topic independent features is hard and trained models with hand crafted features in one domain may not work in another domain. In this study we used a semi-supervised neural language model which is known as document embeddings for authorship attribution problem. This method showed significant improvements over bag-of-words representations in a well-known dataset.