Content for Intelligent Solutions

 Intellisophic is the worlds largest producer of taxonomic content for use in advanced information and intelligence applications. Our deep subject matter expertise covering almost every subject area provides immediate access to millions of topics through our cloud server.

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The Linkapedia Knowledge Hub.


Experts agree that up to 85% of enterprise’s most valuable data is unstructured; data which is locked in documents, email, web-pages, call center records, CRM sales notes, news feeds, resumes, reports and free-text fields within structured records. This information is arguably the most important data an enterprise owns. Unfortunately, due to the complexity of systematically understanding this information, it has been mostly ignored by the Enterprise Applications in use today.

  • Enterprise Search & Retrieval
  • Categorization & Classification
  • Portal Infrastructure
  • Content & Knowledge Management
  • Data Warehousing
  • Business Intelligence
  • Compliance Management
  • Social Networking
  • Electronic Discovery
  • Government Intelligence



Taxonomic content is the key to next generation Content Intelligence solutions. Building a taxonomy for most organizations can take 2-3 hours per concept, resulting in taxonomies too small and restricted to cover the entire business effectively. Previous attempts at automation failed to provide taxonomies with the embedded knowledge that experts provide.


Guide to Concept Taxonomies

Taxonomic content is the key to next generation Content Intelligent solutions. Intellisophic provides taxonomic content to fuel content intelligence applications. Taxonomic content is critical to enterprise applications which leverage knowledge trapped in unstructured data such as documents, emails, corporate correspondence, reports, memos, call center notes, CRM notes, contracts, IRC chatter, instant messages, web pages and […]

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Leveraging Collective Knowledge

Taxonomies are well accepted knowledge tools for large-scale text indexing. But taxonomies in practice are implemented as shallow hierarchies for navigation and categorization, or as controlled dictionaries and thesauri – all using only a string as the terminal concept representation. This paper presents an approach called orthogonal corpus indexing (OCI) which generates large scale concept […]

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Concept Tagging for Data Enrichment