@techreport{TD:100435,
	att_abstract={{  There are several theories regarding what influences prominence assignment in English noun-noun compounds. We developed corpus-driven models for automatically predicting prominence assignment in noun-noun compounds using feature sets based on two such theories: the informativeness theory and the semantic composition theory. The evaluation of the prediction models indicate that though both of these theories are relevant, they account for different types of variability in prominence assignment.                                              }},
	att_authors={tm330a, sb7658},
	att_categories={C_IIS.11},
	att_copyright={{ISCA}},
	att_copyright_notice={{The definitive version was published in Proceedings of ACL-HLT 2011. {{, 2011-06-19}}
}},
	att_donotupload={},
	att_private={false},
	att_projects={Natural_Voices},
	att_tags={Nominals, Relative prominence,  Informativeness measures,  Synsets},
	att_techdoc={true},
	att_techdoc_key={TD:100435},
	att_url={http://web1.research.att.com:81/techdocs_downloads/TD:100435_DS1_2012-09-06T15:46:03.525Z.pdf},
	author={Taniya Mishra and Srinivas Bangalore},
	institution={{Proceedings of ACL-HLT 2011}},
	month={June},
	title={{Predicting Relative Prominence in Noun-Noun Compounds}},
	year=2011,
}