LANGUAGE ANALYTICS
CAAT provides language analytics on a number of levels. As a fully Unicode® compliant platform, CAAT is language agnostic and can work in any language that can be represented in the Unicode encoding system. This means that CAAT works within languages that are Unicode-compliant: searches can be performed in any language on text written in that same language, a feature becoming increasingly important in a global business world.
CAAT also provides a Language Identification module, wherein CAAT will identify the primary language of a document. Optionally, it can also find the full complement of languages present in a document, and note the segments associated with each. This greatly speeds workflows where documents need to be sorted before further processing, such as Machine Translation.
CAAT also works across languages offering a unique and compelling cross-lingual language analytics capability. The same mechanism that allows CAAT to train itself to identify concepts across an index of documents is employed to train CAAT to correlate those languages themselves. Through use of parallel corpora (sets of identical documents that have been already translated into different languages), CAAT learns how a given concept is expressed across languages. This training is a simple indexing function. Once trained, CAAT can search for concepts across languages: it can use a concept expressed in English to find similar concepts in French, Japanese and/or Arabic for example, with no translations required. Other CAAT functions like Concept-based Categorization and Dynamic Clustering also operate in this cross-lingual mode.
In order for CAAT to understand specific technology and issues in this cross-lingual mode, groups of identical translated documents covering these topics can easily be added to the corpora. CAAT can then be "trained" to understand these specific concepts and topics and users can search in one language yet find relevant documents present in other languages without prior translation.
