TME 5 core linguistic modules

TME 5 finds meaning in content

• Concept Extraction

  TME 5 identifies meaningful information from documents, be they keywords or phrases that are given explicit mention. Using linguistic algorithms, it then extracts the core concepts of content.

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• Entity Extraction

  This module locates and extracts names of people, organizations, locations, currencies, dates, trademarks/products and URLs.

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• Categorization

  Categorization is crucial for developing clean, standardized, readable metadata. It indexes and classifies documents against custom or generic taxonomies (IPTC, ICB and more).

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• Summarization

  Nstein's summarizer automatically identifies and extracts the most relevant sentences in a document, creating on-the-fly and highly pertinent summaries of content.

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• Sentiment Analysis

  Identify the tone of any given article, sentence and entity, weighting it along a positive-negative spectrum, and unlock the power of contextual advertising, brand & public image monitoring and more.

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• Similarity

  Nstein's TME can identify rich, nuanced similarities between content-pieces, a central element in creating an unrivaled contextual experience for readers, while facilitating easier document research.

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