Paper Info
Title
Automatic metrics for genre-specific text quality
Abstract
To date, researchers have proposed different ways to compute the readability and coherence of a text using a variety of lexical, syntax, entity and discourse properties. But these metrics have not been defined with special relevance to any particular genre but rather proposed as general indicators of writing quality. In this thesis, we propose and evaluate novel text quality metrics that utilize the unique properties of different genres. We focus on three genres: academic publications, news articles about science, and machine generated text, in particular the output from automatic text summarization systems.
Year
Venue
Keywords
2012
HLT-NAACL
different way,different genre,special relevance,general indicator,particular genre,automatic metrics,genre-specific text quality,novel text quality metrics,automatic text summarization system,news article,discourse property,academic publication
Field
DocType
Citations 
Automatic summarization,Text mining,Information retrieval,Computer science,Coherence (physics),Readability,Natural language processing,Artificial intelligence,Syntax
Conference
3
PageRank 
References 
Authors
0.41
22
1
Name
Order
Citations
PageRank
Annie Louis144324.78