While manually tagging or categorizing items and documents in Microsoft SharePoint 2010 using the new managed metadata and enterprise keyword columns, 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.

 

Fig.: While tagging an item or document, Tag Suggester - additionally to the out-of-the-box auto-complete list - displays a suggestion list, based on given Term Store taxonomies, tag rules, item properties, context and document content.

The Tag Suggester für SharePoint 2010 offers the following 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 based 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.
• 100% SharePoint 2010 technology: Completely based on SharePoint 2010 Enterprise Metadata Management API.
• Seamless integration with other SharePoint Knowledge Management Suite components.

The SharePoint Tag Suggester is available as component of the Knowledge Management Suite for SharePoint 2010. The solution comes with a robust installer to allow it to be easily deployed within any SharePoint environment. It is available for Microsoft SharePoint Server 2010 (any editions).

Please register to download a shareware version of the Knowledge Management Suite for SharePoint for free usage now. Use the registration form on this page or contact sales@layer2.de . 

With the complete FREE shareware version you can download and use a feature-limited solution. To buy a license for this product, please click the shopping card symbols on this page.

The product is licensed on a per server base (one time fee). No additional clients licenses (CALs) are required. If you have several servers (e.g. in a farm scenario) all servers have to be licensed. You need a license for every web frontend server. Infrastructure server, e.g. for indexing or search don't need a license. You can optionally buy Software Assurance (SA) for free updates / upgrades to protect your investment.

For more information about licensing please check our FAQs or contact sales@layer2.de directly.

Please use the SharePoint 2010 Power Shell script (*.ps1) provided to install or upgrade the product. Use the "Run as Admin" option of the context menu (right click). After sucessfull installation please activate the feature on site collection level as a site collection administrator.

Fig.: Before using the Tag Directory Web Part is has to be activated in the Site Collection Features.

Shareware Limitations:

• The "Suggest" button is disabled for some seconds after tagging dialog pops up.

Please request a time limited full featured license for better evaluation, if required.

Known Issues:

• There were issues to suggest tags for a newly created item / document or unsaved changes in update forms with previous versions. That is fixed with the current version.
• Multi-line fields of type „Enhanced Rich Text“ are currently not supported with Tag Suggester
• Rules are currently supported, but the Taxonomy Manager is required to add / edit it
• Attachements are generally considered now, but not for newly created items with Tag Suggester
• Folder-Names are generally considered now for tagging, but not for newly created items with Tag Suggester

Did you found any additional issues? Please give feedback.

The simplicity and popularity of collaborative tagging as an information organization approach comes at the expense of several limitations. 

Manual content categorization / tagging

Traditionally, content has been categorized by subject experts, who manually reviewed documents and matched them to categories within a taxonomy. Despite the costs involved in manual categorization, it is perceived to have one key advantage: 100% accuracy. This is not necessarily true:

• Firstly, people choose tags based on their personal opinions, their knowledge background and their preferences. Subject experts may not have the bigger picture. An expert categorizing documents in his field does not necessarily possess expertise in other subjects - other parts of the taxonomy. An article about a businessman purchasing a baseball team may be reviewed by a sports expert, and categorized in the "Basketball" category, but not in one of the more specific subcategories of the "Mergers and Acquisitions" category.
• Furthermore, users may be describing the same object based on different granularity. This creates a noisy tag space and thus makes it harder to find material tagged by other users.
• Secondly, people may use polysemous words (a word that has many related senses) in order to tag the web resources. The lack of semantic distinction in tags can lead to inappropriate connections between items.
• Another problem is that different tags, which are either synonymous or have closely related meaning increase data redundancy, leading to reduced recall of information.
• Last, but not least, people tend to assign a very small number of tags to an object.

In addition, manual categorization it completely impractical for very large repositories of data that grow at a fast pace - exactly the case for most modern organizations.

All these limitations have led researchers to develop methods that assist users in the tagging process, by automatically suggesting an appropriate rich set of tags, in order to avoid the aforementioned obstacles.

Automatic rule-based content categorizing / tagging

Using this approach, information experts attempt to define the discriminating properties of categories using a set of rules. These rules may be simple (e.g. "does the word 'snow' appear in the document"), or use more complex operators (e.g. "does the word 'snow' appear together with the word 'skate'"). In order to find precise rules that distinguish similar categories (for example, "Financial Planning" and "Investment Banking") one needs substancial expertise in the subject being covered. This approach's reliance on human-comprehensible rules is an advantage, because it allows an organization to leverage existing knowledge and expertise. It needs time, effort and expertise to create the rules - but the results are absolutely predictable and can be improved step by step.