Columbia University in the Novelty Track at TREC 2004

[摘要] Our system for the Novelty Track at TREC 2004 looks be yond sentence boundaries as well as within sentences to identify novel, nonduplicative passages. It tries to iden tify text spans of two or more sentences that encompass minisegments of new information. At the same time, we avoid any pairwise comparison of sentences, but rely on the presence of previously unseen terms to provide evidence of novelty. The system is guided by a number of parameters, both weights and thresholds, that are learned automatically with a randomized hillclimbing algorithm. During learning, we varied the target function to produce configurations that emphasize either precision or recall. We also implemented a straightforward vectorspace model as a comparison and to

[学科分类] 社会科学、人文和艺术（综合）