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Thus, novelty mining can help to single out novel information out of a massive set of text documents.
Plagiarism in text documents can be done in many ways.
The digital archive collects video, print images and text documents.
In this paper, we show how the required semantic relations can be learned from a large collection of text documents.
To this end, we first induce a conceptual space from the text documents, using multi-dimensional scaling.
For scanning text documents, use the "line art" settings.
Students prepared PowerPoint files and text documents to post on a project website.
Sentiment analysis is a critical task of extracting subjective information from online text documents.
Two different classifiers are designed based on the two different representation models of the text documents.
An enhanced S-VSM model will be considered for the constructive representation of text documents.
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