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Knowledge Management

Silverpeas makes it easier to display the individual and tacit knowledge of a company's employees, while providing them various support means (Expert Directory, FAQ, multimedia documents, blogs, Wiki). Silverpeas ranks information, and suggests texts.

The knowledge management is based on :

 

The taxonomy that makes it possible to tag the knowledge

Expert directories and the social network's news feed to locate unknown experts,

Instant messaging enables requesting immediate and direct help from an expert...

The semantic mechanisms suggest texts ("see also")

The semantic mechanism classifies knowledge into clusters

The applications offers support that are adapted to various forms of knowledge base.

 

SilverpeasTM Knowledge Management is built around 4 applications:

  • A directory of Experts
  • A notification system
  • A knowledge database
  • A social network (wall and dashboard)


The components promote the sharing and localization of knowledge, and are directly related to the classification scheme by theme.

Users can use an existing axis to classify their questions.

Users identified as competent experts on themes, receive notifications and can publish their answers.

The knowledge base can be consulted by readers with read rights. Component animators are in charge of closing and moving exchanges.

The knowledge base component allows the FAQ tree structure to be organised by theme.

FAQ can be accessed via the tree structre or the search engine.

The applications settings can be adjusted using a simple administration interface needing only basic IT skills.


Associating components with the Experts directory:

By associating the applications with the experts directory, all parts can be associated to a technical expert, with the authorization to contribute and answer questions according to their field of expertise

The Experts directory allows employees to be classified according to their skills, in association with classification plan. Experts are immediately identified and localized.