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Multidocument summarization has gained popularity in many real world applications because vital information can be extracted within a short time. Extractive summarization aims to generate a summary of a document or a set of documents by ranking sentences and the ranking results rely heavily on the quality of sentence features. However, almost all previous algorithms require hand-crafted features for...
Multi-document summarization has gained popularity in many real world applications because significant information can be obtained within a short time. Extractive summarization aims to generate a summary of a document or a set of documents by ranking sentences, whose performance relies heavily on the quality of sentence features. However, almost all previous algorithms require hand-crafted features...
Measuring similarity has a wide range of application in information retrieval, machine translation or other related fields. In this paper, we proposed a text similarity computation based on improved optimal assignment model, which combine the improved Hungarian algorithm with the semantic similarity of terms to obtain the maximum semantic similarity between two documents or between a query and a document...
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