Text summarization in data mining

Abstract

Text summarizers automatically construct summaries of a naturallanguagedocument. This paper examines the use of text summarization withindata mining, identifying the potential summarizers have for uncovering interestingand unexpected information. It describes the current state of the art incommercial summarization and current approaches to the evaluation of summarizers.The paper then proposes a new model for text summarization andsuggests a new form of evaluation. It argues that for summaries to be truly usefulwithin data mining, they must include concepts abstracted from the text inaddition to sentences extracted from the text. The paper uses two news articlesto illustrate its points.