Regardless of industry, end user search should “just happen”.
Without the combination of semantic (the meaning of content) and syntactic (document type, date, author) metadata, utilizing metadata to drive business agility will remain a never ending challenge and can never be a reality. Concept Searching has solved the problem with conceptClassifier for SharePoint that includes automatic semantic metadata generation, automatic classification, and taxonomy management.
Utilizing concept extraction and compound term processing conceptClassifier automatically identifies the most significant patterns in any text and uses these com-pound terms to rank results based on an understanding of meaning rather than simply based on finding the required key words ("concepts in context‟). This is significantly more adaptive and flexible than exact phrase or proximity searching. Queries can be expressed in natural language, without the need for complex query syntax associated with traditional Boolean techniques. Fully integrated with MOSS, Microsoft Enterprise Search and the Office client suite conceptClassifier for SharePoint is SOA compliant and delivered as Web Parts. The versatility of the technologies and full integration with MOSS makes it extendable to any enterprise application that needs access to unstructured information such as Search, ECM, Document Management, Records Management, and Web Content Management.
conceptClassifier™ for SharePoint is fully integrated with Microsoft® Enterprise Search and does not need a seperate index. From the familiar SharePoint interface users can use taxonomy based navigation or faceted navigation.
Taxonomy based navigation will present users with a hierarchial structure for browsing and searching relevant categories. Faceted navigation presents the user automatically with clusters that contain documents grouped according to the broad concept of the cluster or facet.
The technology can be further extended by associating metadata with individuals in the organization enabling expert identification when an end user is searching for information pertinent to a specific subject.