Paper: Identifying Topics By Position

ACL ID A97-1042
Title Identifying Topics By Position
Venue Applied Natural Language Processing Conference
Session Main Conference
Year 1997
Authors

This paper addresses the problem of iden- tifying likely topics of texts by their posi- tion in the text. It describes the automated training and evaluation of an Optimal Posi- tion Policy, a method of locating the likely positions of topic-bearing sentences based on genre-specific regularities of discourse structure. This method can be used in applications such as information retrieval, routing, and text summarization.