Verity Releases K2 Enterprise 5.0

Jun 24, 2003

Verity Inc. has announced the release of 5.0 of its Verity K2 Enterprise (K2E) software. The latest version of the company's flagship product includes new features and functions designed to better allow enterprises to create or expand intellectual capital management systems that match their global scale and scope. Verity K2E 5.0 includes enhancements to intellectual capital management capabilities delivered in prior releases of the software. A more powerful recommendation engine now suggests individual documents, similar users' queries, categories of documents as well as experts, communities of interest, and other user-defined elements. When deployed with the Verity Federator announced earlier this year, this extended social networking engine enables recommendation of documents even if they are beyond the content indexed by Verity K2E. Dynamic taxonomies, also new with version 5.0, allows users to create and share their own taxonomies, participate actively in the enhancement of their organizations' taxonomies, and enables the engine to automatically analyze and recommend related categories. In addition to providing content organization technologies from business rules to automatic classification and thematic mapping, Verity K2E 5.0 also offers the ability to include active and passive recommendation tools to assist in the development and management of taxonomies. K2E supports document-level security based on integration with identity management and single sign-on solutions from IBM, Netegrity, Oblix and RSA Security, which provides global enterprises more effective ways to build a secure intellectual capital management system. K2E 5.0 also supports more than 70 languages, now including Arabic. New multi-language collections, in conjunction with Unicode Locales, deliver linguistic analysis functionality that lets users retrieve relevant results from content in a single selected language, or across all information regardless of language. Content is automatically identified by language type, tagged, and then routed to multiple- or specific-language collections, depending on administrative preference, which helps to decrease development and maintenance costs by eliminating the need to build separate collections for each language in use.