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SKATeR

SKATeR

SKATeR
SKATeR will advance the state of the art in non-extractive text summarization tecniques by using knowledge induced from textual data. Summarization in the SKATeR scenario will be based on the creation of concise summaries of events by the...

The state of the art in text summarization currently is sentence extraction. This method of producing summaries, in spite of its robustness, is rather limited since sentence extracts have well known problems of cohesion and coherence. The research proposed in SKATeR will overcome the limitation of current summarization systems by investigating, proposing, and implementing corpus-based empirical approaches to model the content of documents and abstractive summaries. The success of the technology developed in STAKeR will be demonstrated in the context of knowledge-based summarization.