Representation of textual documents by the approach wordnet and n-grams for the unsupervised classification (clustering) with 2D cellular automata: a comparative study.
Reda Mohamed HamouAhmed LehirecheAhmed Chaouki LokbaniMohamed RahmaniPublished in: Comput. Inf. Sci. (2010)
Keyphrases
- cellular automata
- unsupervised classification
- wordnet
- n gram
- word sense disambiguation
- unsupervised learning
- co occurrence
- natural language processing
- clustering ensemble
- data clustering
- semantic information
- language model
- semantic relations
- part of speech
- semantic similarity
- text documents
- text clustering
- text classification
- knowledge base
- keywords
- artificial intelligence
- bag of words
- clustering algorithm
- k means
- text mining
- machine learning
- textual data