QuantumText14 utilizes Hilbert Technology’s unique and patented approach of storing and organizing data to enable the rapid identification of the most relevant documents in large volumes of textual data in minutes, rather than the days or weeks required by the closest alternative systems.
With QuantumText14, an analyst can quickly cull the most relevant documents from a massive corpus of information within a time-limited window of analysis and return the most relevant documents with precision and recall faster than any known alternative. The culling or winnowing down process does not rely on key word or phrase search. Descriptive paragraphs, or documents in their entirety, can be specified as criteria against which every other document in a specified corpus is ranked in terms of content similarity and closeness.
Here’s how it works: An analyst either creates or selects a document that he or she wants to use as an “exemplar” (e.g., the ranking criteria.) Then, the full text of that exemplar document — at the word level — is scrutinized and compared against every other document in the entire large corpus of documents — also at the word level, resulting in a prioritized ranking with scoring commensurate with each document’s content relevance and correlation to the exemplar. The process is driven by Hilbert Technology’s core processing engine, the Hilbert Engine, and an advanced indexing system that, working together, return results with precision and recall at very high speed without requiring any advanced data tuning.
QuantumText14 can be applied to text in all natural languages — alphabet and logogram based languages, such as East Asian. The system can operate as a standalone or be integrated as a subsystem in large enterprise eDiscovery offerings encompassing customer service, technical support and forensic analysis.
Read the full story at http://www.prweb.com/releases/2014/02/prweb11554785.htm
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