Abstract
We investigate the problem of text segmentation by topic. Applications for this task include topic tracking of broadcast speech data and topic identification in full-text databases. Researchers have tackled similar problems before but with different goals. This study focuses on data with relatively small segment sizes and for which within-segment sentences have relatively few words in common making the problem challenging. We present a method for segmentation which makes use of a query expansion technique to find common features for the topic segments. Experiments with the technique show that it can be effective.
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© 1997 Springer-Verlag Berlin Heidelberg
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Ponte, J.M., Croft, W.B. (1997). Text segmentation by topic. In: Peters, C., Thanos, C. (eds) Research and Advanced Technology for Digital Libraries. ECDL 1997. Lecture Notes in Computer Science, vol 1324. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0026725
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DOI: https://doi.org/10.1007/BFb0026725
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