Oh no not again – is Java a programming language, coffee, or an island?
Remember when search was becoming a big deal and it seems everyone was using the above example to illustrate the ambiguity in words? I hate to admit, I used it too.
SharePoint Server 2013 has added a new Content Search Web Part that displays content that was crawled and added to the search index. To display content in the Content Search Web Part, you specify a query in the Web Part. This query is automatically issued, and it returns results from the search index when users browse to a page that contains the Content Search Web Part. The Content Search Web Part is especially powerful when it is used in combination with managed navigation and category pages. For example, in an Internet business scenario where a product catalog is displayed, a term within the term set specified for managed navigation is associated with a specific category page. You can specify that a query in a Content Search Web Part on a category page use the current navigation category as part of the query. For example, when users browse a category, such as Computers, a query is issued from the Content Search Web Part to return all items from the search index that are specified as Computers. Similarly, when users browse to the category Audio, the same Content Search Web Part on the same category page will display items in the search index that are specified as Audio.
The above example works great in the catalog scenario. But what about our term java? Once java is added to the search index what do my search results contain? Microsoft has radically changed search in SharePoint 2013 and all for the better. But fundamentally, the search experience really won’t change unless the index can capture the essence or meaning of content that can be placed in the search index to achieve relevant search results without manual intervention.
Our auto-classification does just that – for all versions of SharePoint. By identifying the most significant patterns in any text, the concepts captured are used to generate metadata based on an understanding of conceptual meaning. This eliminates the requirement for an individual to read a document and subjectively apply metadata to that document. This ability to identify ‘concepts in context’ eliminates inconsistent or non-existent tagging processes, and overcomes different publishing conventions that may exist within the organization.
Running natively and fully integrated with the Term Store, the taxonomy component in conceptClassifier for SharePoint can consistently apply conceptual metadata to content and auto-classify to the term store metadata model solving the challenge of applying the metadata to thousands of documents and eliminating the need to depend on the end user community to correctly tag content. The taxonomy manager component functions bi-directionally with the term store where changes can be made in the term store or in the taxonomy manager. This added functionality assists in expediting the development of the metadata models, offers sophisticated refinement capabilities, and significantly reduces on-going maintenance.
With faceted navigation using the term store/taxonomy I can quickly find out once and for all if Java is a programming language, a coffee, or an island.