Segmentation and Detection at IBM : Hybrid Statistical Models and Two-tiered Clustering
نویسندگان
چکیده
Models and Two-tiered Clustering M. Franz J.S. McCarley T. Ward W.-J. Zhu IBM T.J. Watson Research Center P.O. Box 218 Yorktown Heights, NY 10598 ABSTRACT IBM's story segmentation uses a combination of decision tree and maximum entropy models. They take a variety of lexical, prosodic, semantic, and structural features as their inputs. Both types of models are source-speci c, and we substantially lower Cseg by combining them. IBM's topic detection system introduces a minimal hierarchy into the clustering: each cluster is comprised of one or more microclusters. We investigate the importance of merging microclusters together, and propose a merging strategy which improves our performance.
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