Search Results for "common"

go-i18n is a Go package and a command that helps you translate Go programs into multiple languages. Supports pluralized strings for all 200+ languages in the Unicode Common Locale Data Repository (CLDR). Code and tests are automatically generated from CLDR data. Supports strings with named variables using text/template syntax. Supports message files of any format (e.g. JSON, TOML, YAML). Use goi18n extract to extract all i18n.Message struct literals in Go source files to a message file for translation. ...

...Key localization file formats are supported, including Gettext PO, XLIFF, Java .properties, PHP arrays and many more supported by the Translate Toolkit. Ensures the best quality localizations by automatically detecting common errors made by translators. Integrates user suggestions, terminology, Translation Memory, Machine Translation, and more. A number of translation projects for a number of languages can be hosted on Pootle. Teams can manage their files, permissions, projects, and translate on-line. Files can be downloaded for offline translation. Delegate to your translators and allow them to commit directly to your version control systems. ...

Semantic Assistants support users in content retrieval, analysis, and development, by offering context-sensitive NLP services directly integrated in standard desktop clients, like a word processor, and web information systems, like a wiki.

... - BioC-formatted corpora - BioC tools that work with BioC corpora BioC goals - simplicity - interoperability - broad use - reuse There should be little investment required to learn to use a format or a software module to process that format. We are interested in reuse, and we focus on common NLP tasks that are broadly useful for textmining.

BANNER is a named entity recognition system intended primarily for biomedical text. It uses conditional random fields as the primary recognition engine and includes a wide survey of the best techniques described in recent literature.

PatchCatcher uses suffix arrays to detect common types of patchwriting among scientific papers.

This program is made to address two most common issues with the known classifying algorithms. First, over-training and second, shortage of data for a training of categories. Instead, each TXT file is a category on its own, rather than an assigned category. In a way, this is similar to clustering but not really a clustering algorithm since there is some training involved. The summarizer from Classifier4J has been adjusted to accept two inputs (lets call them A and B).

A system to perform analysis of large documents for the purpose of cataloging similar documents. Similarity is based upon contextual analysis of these documents done by identifying common words and proper nouns.