1,721,075 research outputs found

    Dai dati alla conoscenza. Statistica per le decisioni.

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    Centrality measures for text clustering

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    Text clustering is an unsupervised process of classifying texts and words into different groups. In literature, many algorithms use a bag of words model to represent texts and classify contents. The bag of words model assumes that word order has no signicance. The aim of this article is to propose a new method of text clustering, considering links between terms and documents. We use centrality measures to assess word/text importance in a corpus and to sequentially classify documents

    A multilevel model to assess job-competence of graduates

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    Uno strumento per migliorare la qualità

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