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Input document set.

Open image in new window Fig. 1 An example of input document.

Information Overload The statistic-based methods exploit external text corpus to enrich the input document.

The detail workflow of TC using LDABoost is: 1. Input document set.   2.

The schemes aim to distinguish the content of the input document image, such as the ad, email, news and report.

Thus, we focus on studying unsupervised methods to extract keyphrases from a single input document (e.g., news and article).

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After keyword extraction, input documents and the document index are fetched to the Encryption block.

Validation of input documents is at the heart of the CMLLite approach.

The input documents are ready for encryption once the indexing is finished.

The input documents below should all result in a ValidationResult of VALID and the ValidationReport MUST NOT contain info elements.

There is no such restriction on info elements and these may occur for input documents that otherwise conform completely to the convention.

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