model,13-4-P06-3007,ak <term> PageRank algorithm </term> on the <term> event map </term> constructed from documents . Experimental
other,11-3-P06-3007,ak important contents by frequency of <term> events </term> . With <term> relevant approach </term>
other,12-2-P06-3007,ak <term> event terms </term> and associated <term> event elements </term> . With <term> independent approach </term>
other,4-2-P06-3007,ak approaches </term> . In this paper , <term> events </term> are defined as <term> event terms </term>
other,8-2-P06-3007,ak , <term> events </term> are defined as <term> event terms </term> and associated <term> event elements
tech,1-3-P06-3007,ak associated <term> event elements </term> . With <term> independent approach </term> , we identify important contents
tech,1-4-P06-3007,ak frequency of <term> events </term> . With <term> relevant approach </term> , we identify important contents
tech,2-1-P06-3007,ak similarity </term> . We investigate <term> independent and relevant event-based extractive mutli-document summarization approaches </term> . In this paper , <term> events </term>
tech,9-4-P06-3007,ak we identify important contents by <term> PageRank algorithm </term> on the <term> event map </term> constructed
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