Language-independent multi-document text summarization with document-specific word associations

The goal of automatic text summarization is to generate an abstract of a document or a set of documents. In this paper we propose a word association based method for generating summaries in a variety of languages. We show that a robust statistical method for finding associations which are specific to the given document(s) is applicable to many languages. We introduce strategies that utilize the discovered associations to effectively select sentences from the document(s) to constitute the summary. Empirical results indicate that the method works reliably in a relatively large set of languages and outperforms methods reported in MultiLing 2013.

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