Measures for Term and Sentence Relevances: an Evaluation for German

Abstract

Terms, term relevances, and sentence relevances are concepts that figure in many NLP applications, such as Text Summarization. These concepts are implemented in various ways, though. In this paper, we want to shed light on the impact that different implementations can have on the overall performance of the systems. In particular, we examine the interplay between term definitions and sentence-scoring functions. For this, we define a gold standard that ranks sentences according to their significance and evaluate a range of relevant parameters with respect to the gold standard.

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