Discovery of Frequent Word Sequences in Text
Proceedings of the ESF Exploratory Workshop on Pattern Detection and Discovery
Authorship Attribution with Support Vector Machines
Applied Intelligence
Augmenting Naive Bayes Classifiers with Statistical Language Models
Information Retrieval
Effective and scalable authorship attribution using function words
AIRS'05 Proceedings of the Second Asia conference on Asia Information Retrieval Technology
A new algorithm for fast discovery of maximal sequential patterns in a document collection
CICLing'06 Proceedings of the 7th international conference on Computational Linguistics and Intelligent Text Processing
Tensor Space Models for Authorship Identification
SETN '08 Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications
A Web-Based Self-training Approach for Authorship Attribution
GoTAL '08 Proceedings of the 6th international conference on Advances in Natural Language Processing
A survey of modern authorship attribution methods
Journal of the American Society for Information Science and Technology
Using the Web as corpus for self-training text categorization
Information Retrieval
Authorship attribution and verification with many authors and limited data
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Particle Swarm Model Selection for Authorship Verification
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Automatic authorship attribution for texts in croatian language using combinations of features
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part II
Local histograms of character N-grams for authorship attribution
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Keyword extraction based on sequential pattern mining
Proceedings of the Third International Conference on Internet Multimedia Computing and Service
A weighted profile intersection measure for profile-based authorship attribution
MICAI'11 Proceedings of the 10th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
| Hi-index | 0.00 |
Authorship attribution is the task of identifying the author of a given text. The main concern of this task is to define an appropriate characterization of documents that captures the writing style of authors. This paper proposes a new method for authorship attribution supported on the idea that a proper identification of authors must consider both stylistic and topic features of texts. This method characterizes documents by a set of word sequences that combine functional and content words. The experimental results on poem classification demonstrated that this method outperforms most current state-of-the-art approaches, and that it is appropriate to handle the attribution of short documents.