Metadata is used to facilitate the understanding, use and management of data. In a library for example, metadata for a book would typically include a description of the content, the author, the publication date and the physical location.

A tag is a descriptor used to facilitate searches. Tags are keywords or phrases associated with a single content object such as an article. For example, a Web article might display the tags Baseball, Red Sox, Tickets, Away Games, and Discounts, with each link leading to an index listing web pages which use that tag. This allows a reader to quickly locate all pages which have been associated with the term Red Sox, for example. If the server supports tag searching, a reader would be able to find all pages that use a particular set of tags.

Descriptive metadata (that is, tags), provides information on individual content samples, whereas structural metadata (that is, the metadata generated by Nstein TME) is the result of analysis of multiple content samples and evaluation of data relationships. This process makes it possible to perform complex filter and search operations, and to generate categorical lists.

The Semantic footprint page used in this procedure is used to supplement the TME-generated metadata with additional user-entered data. This procedure applies to articles, news items, collections, photos and slideshows.

Manually-added metadata tags are especially useful for photos or slideshows, which, being representative rather than text entities, don't typically include a lot of words for the TME to mine.

Sentiment anlysis :

This pane provides metrics on the Tone and Subjectivity of the content object.

Semantic footprint:

When you are done, select Save or Check-in (according to your selected lock mode) to save your tags.