@article {15295,
	title = {Syntactic sentence compression in the biomedical domain: facilitating access to related articles},
	journal = {Information Retrieval},
	volume = {10},
	year = {2007},
	month = {2007///},
	pages = {393 - 414},
	abstract = {We explore a syntactic approach to sentence compression in the biomedical domain, grounded in the context of result presentation for related article search in the PubMed search engine. By automatically trimming inessential fragments of article titles, a system can effectively display more results in the same amount of space. Our implemented prototype operates by applying a sequence of syntactic trimming rules over the parse trees of article titles. Two separate studies were conducted using a corpus of manually compressed examples from MEDLINE: an automatic evaluation using Bleu and a summative evaluation involving human assessors. Experiments show that a syntactic approach to sentence compression is effective in the biomedical domain and that the presentation of compressed article titles supports accurate {\textquotedblleft}interest judgments{\textquotedblright}, decisions by users as to whether an article is worth examining in more detail.},
	doi = {10.1007/s10791-007-9029-5},
	author = {Jimmy Lin and Wilbur,W. J}
}
