Paper Info
Title
Implementing a characterization of genre for automatic genre identification of web pages
Abstract
In this paper, we propose an implementable characterization of genre suitable for automatic genre identification of web pages. This characterization is implemented as an inferential model based on a modified version of Bayes' theorem. Such a model can deal with genre hybridism and individualization, two important forces behind genre evolution. Results show that this approach is effective and is worth further research.
Year
Venue
Keywords
2006
ACL
implementable characterization,web page,genre hybridism,automatic genre identification,inferential model,genre evolution,important force,modified version,web pages
Field
DocType
Volume
Web page,Computer science,Natural language processing,Artificial intelligence,Bayes' theorem
Conference
P06-2
Citations 
PageRank 
References 
10
0.68
13
Authors
3
Name
Order
Citations
PageRank
Marina Santini1252.25
Richard Power248645.19
Roger Evans334455.12