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Turning content into assets
Benefits
Extract the inherent monetary value from content
Connect people with relevant content
Prepare for the semantic Web
Create portable, channel-independent content
Create new business opportunities
Information-rich organizations need to extract meaning, nuance, and context from vast amounts of unstructured content in order to expose and leverage its true business potential. Open Text Content Analytics (formerly Nstein Text Mining Engine (TME)) helps you do just that. By deriving the semantic nature of content, whether that content resides in the Open Text ECM Suite or any other corporate information repository, Content Analytics delivers value by enabling you to:.
Connect people with relevant content: Content Analytics enriches content with semantic metadata that makes it vastly more findable, visible, and search-engine optimized (SEO). This increased visibility ensures that external content remains associated with a particular brand.
Prepare for the semantic Web: Content Analytics is designed to optimize content for the semantic Web by understanding its meaning and extracting its full value. Content Analytics turns content into knowledge that is easy to find, creatively re-combine, and share.
Create portable, channel-independent content: Write once, publish many times. Content Analytics standardizes and enriches content simultaneously, making it ready for delivery across multiple digital channels. Whether you are trying to go mobile, port to print, or syndicate, the clean, intelligent XML that Content Analytics generates makes content ready for multi-channel delivery.
Create new business opportunities: With content in a highly structured, findable, enriched, and portable format, you can contextually associate it with appropriate advertising content and easily segment and retrieve it to develop targeted microsites, license it, or syndicate it.
Reduce content-related costs: Content Analytic's automated tagging feature helps reduce content-related costs by categorizing content properly and making it easy to research and repurpose.
Features »
The main features of Content Analytics include:
Concept Extraction: Concept Extraction is a linguistic and statistical analysis engine that is used to identify the central concepts (uncontrolled vocabulary) contained in any document.
Entity Extraction: Entity Extraction locates and extracts places, people, organizations, trademarks/products, and just about anything else you can think of. This is a powerful way to sort, visualize, and organize data.
Categorization: Categorization automatically indexes and sorts documents by category and identifies relevancies.
Sentiment Analysis: Sentiment Analysis detects the subjective nature of a document, along with its tonality (positive, negative, neutral).
Summarization: Summarization identifies key sentences in a document and uses them to create a summary, liberating editorial staff from an otherwise menial task.
Similarity Service: Similarity Service identifies similarity between documents. Using the metadata generated by the other features of Content Analtyics, Similarity Service links documents based on their exhaustive profiles.
Automatic Language Detection: Content Analytics automatically identifies the language of a given document. It detects the following languages out-of-the-box: English, French, German, Arabic, Chinese (simplified), Czech, Danish, Estonian, Finnish, Hebrew, Italian, Japanese, Korean, Polish, Portuguese, Russian, Spanish, Thai, Turkish, Ukrainian. Additional languages can be added via customization.
Management Console: The Management Console is used by administrators to modify and maintain authority files in a flexible, simple manner (no programming expertise required).
Resources
Click the links below for more information about Content Analytics:
Related Products
Open Text Semantic Navigation uses Open Text Content Analytics technology to index Web sites and enable visitors to navigate them via semantic concepts.
