We test the technique on the problem of Text Summarization TS. Extractive TS relies on the concept of sentence salience to identify the most important sentences in a document or set of documents. Salience is typically defined in terms of the presence of particular important words or in terms of similarity to a centroid pseudo-sentence. We consider a new approach, LexRank, for computing sentence importance based on the concept of eigenvector centrality in a graph representation of sentences.
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論文翻訳: LexRank: Graph-based Lexical Centrality as Salience in Text Summarization
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