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A corpus is a large collection of texts that can be automatically analyzed for linguistic patterns and structures using interactive tools. Corpus-based language learning has gained prominence in recent years thanks to the advances in computing technologies, such as text mining, searching, and natural language processing. The size and variety of corpora have also grown significantly in recent years...
Composition style is often an important factor in readers' selection of reading materials. For example, a reader may seek out articles written in similar style as his or her favorite writer. We present a new method for providing recommendations based on the composition style. Our algorithm analyzes and encodes the readability index and syntactical structure of a model document, and then searches for...
Many readability tests have been developed to assess the reading difficulty of a text document. However, a typical readability index is a single average number for the entire document, which does not indicate the readability at the paragraph level. In addition, multiple readability indexes often do not correlate well at the paragraph level, leading to variations of readability measurements for paragraphs...
Many readability tests have been developed to assess the reading difficulty of a text document. They are largely based on two categories of readability metrics: word complexity and sentence complexity. However, most of the readability tests assign a single readability index for the entire document, making it difficult to assess how the various readability metrics are distributed across the document...
Data integration is the problem of combining data residing at different sources, and providing the user with a unified view of these data. One of the critical issues of data integration is the detection of similar entities based on the content. This complexity is due to three factors: the data type of the databases are heterogeneous, the schema of databases are unfamiliar and heterogenous as well,...
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