While manually tagging or categorizing items and documents in Microsoft SharePoint 2010 using the new managed metadata column, the Tag Suggester for Microsoft SharePoint Server 2010 automatically offers a set of appropriate content-based category or keyword suggestions, depending on the term store taxonomies and managed metadata, tag rules, item and document properties and metadata, information store context and textual document contents. By default SharePoint 2010 offers an auto-complete feature only. The Web Part is available as part of the Knowledge Management Suite for SharePoint 2010.
Features and benefits:
Increased productivity and precision while tagging SharePoint items and documents manually based on given taxonomies / managed metadata. The system is not only able to suggest many useful tags, but also to discover new and relevant tags, not suggested by any of the human users.
An additional suggest list is displayed with appropriate tags / keywords based on certain term stores / taxonomies.
Taxonomy entry point (root node) is automatically chosen with respect to the current meta data column settings.
List items are processed as well as documents and files located in SharePoint libraries.
Properties (meta data column content) of list items and documents are considered for tagging.
The context of items and documents, e.g. site, list, library, folder is considered for tagging.
The document or file textual contents are considered, if IFilters are installed.
Use of categorization rules is supported (e.g. one term is in document content while another term is not). High performance Microsoft .NET Framework bases rule engine.
Installed IFilters are used for content analysis, e.g. Word, Excel, PowerPoint, PDF and many more).
Fully integrated in default SharePoint tagging dialog. Out-of-the-box features (e.g. auto-complete) are kept working.
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Offers a set of appropriate content-based category or keyword suggestions, depending on the term store taxonomies and managed metadata, tag rules, item and document properties and metadata, information store context and textual document contents.