Sentence examples for large set of documents from inspiring English sources

Latent Semantic Indexing (LSI) is a standard approach for extracting and representing the meaning of words in a large set of documents.

Accordingly, "blanket" requests for confidentiality of a large set of documents are unacceptable.

While some of the replies may be kept confidential, the commission warned that "blanket" requests for confidentiality of a large set of documents are unacceptable.

Another such technological area is that of document clustering; by automatically creating groups (clusters') within a large set of documents, that large set of documents can be divided into consumable parts, and thereby made tractable to a given user or set of users.

Manually tagging entities of all two types in such large set of documents and comparing these entities to those found automatically by the extractor would require a lot of work.

The initial seed, not only has high extraction precision, but because it was created based on a large set of documents (52,000), it can be utilized as a highly reliable training set for ML algorithms across domains, thus eliminating the need for manually tagged training documents.

The initial network training is made on a large set of document images synthetically generated with a suitable tool implemented for this task.

In a world where billions of digitized documents exist, technologies that make large sets of documents more tractable are in significant demand.

We use a value of p = 0.99 in our experiments, modeling a patient user who is willing to review an extensive answer set; this reflects the current behavior of users engaged in systematic review construction, who work their way through large sets of documents returned by Boolean queries.

But examining the larger set of documents from the initial phase of the Skyhook trial against Google is opening a window into Google executives' views on how they sought to reinforce Google's monopoly and collect personal information from its users.

The only difficult part is training the AgroTagger with a new thesaurus; in fact, it requires to build a new MAUI model, which needs a medium-large set of documents already indexed with the specific thesaurus by humans.