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Intelligent searching and classifying

People everyday are under pressure to make the right decisions at the right time, to help achieve this, quick, comprehensive, and understandable searching of data “knowledge” is a necessity. The ever increasing flood of information requires structured organisation of the data found.

Intelligent search mechanism

With the growing information surge, polished search mechanisms have become a requirement for document management systems. onGO DMS meets this challenge with the use of a relational database, this allows for high speed searches on indexed fields. Different search criteria can be arbitrarily combined through logical and/or linking references. In addition any desired combination of user-defined attributes can also be specified.

Search results are clearly displayed in either an explorer/file manager interface or via a web browser. The search criteria can at any time be modified and the search restarted.

Especially complex searches can be stored as an object within onGO DMS and be represented by an appropriate icon, a simple double click can then restart the search, so that a current, dynamic search result is always available.

Full text search

All documents are automatically converted into alpha format; from this a full text index is created. On this index full text searches can be processed, which is as with all other search criteria arbitrarily combinable and storable.

Associative search

The software technology used in the associative search offers an innovative solution for the administration and storing of unstructured digital information, especially files in word processing and HTML formats.

In addition to the standard full text search, several gigabytes of unstructured documents can be intelligently classified and semantically searched. Context-sensitive keywords and linking to similar documents are automatically processed.

The basis of this technology is a sophisticated illustration of associative data, whereby similarities are captured between both terms and text documents. This approach enables the design of a search that warrantees the receipt of only the relevant information requested by the user.

The resulting information becomes substantially more efficient and a set of knowledge management functions to be realised on this architecture:

  • Linking of various databases
  • Creation of personal profiles
  • Cross-linking of persons and contents
  • Creation of a “knowledge pool“
  • Avoidance of redundant data
  • Reduced search times
  • Higher motivation from employees
  • Improved knowledge structure
  • Removal of knowledge deficits
  • Web supported system, no rollout issues
  • User defined interest profiles
  • Active notifications