Conference paper
Unsupervised and supervised clustering for Topic Tracking
Martin Franz, S. McCarley, et al.
SIGIR Forum (ACM Special Interest Group on Information Retrieval)
In this poster we describe experiments in information retrieval using a new method for scoring correlated features. This method uses information about word co-occurrences in the documents ranking high after the initial scoring to reduce combined scores of correlated words. We have experimented with this technique in conjunction with both simple Okapi scoring and a query expansion method using a probabilistic model, improving system performance in the context of TREC standardized tasks.
Martin Franz, S. McCarley, et al.
SIGIR Forum (ACM Special Interest Group on Information Retrieval)
S. Deila Pietra, V. Deila Pietra, et al.
ICASSP 1992
K. Papineni, Salim Roukos, et al.
INTERSPEECH - Eurospeech 1999
G. Iyengar, H.J. Nock, et al.
ICME 2002