The information retrieval feature set contains many features that are generally found helpful in summarization, in particular tf •idf and scores derived from centroid methods.
we used the latent semantic analysis (LSA) feature discussed in (Murray et al., 2005), which attempts to determine sentence importance through singular value decomposition, and whose resulting singular values and singular vectors can be exploited to associate each utterance a degree of relevance to one of the top-n concepts of the meetings (where n represents the number of dimensions in the LSA).