ClearForest announced ClearTags 4.0, a comprehensive auto-tagging platform. The new version, which includes semantic, statistical and structural tagging, expands tagging output and the understanding and value of unstructured content. A new user control panel allows the definition of different tagging schemes for any type of document stream, monitoring the entire tagging process. ClearTags allows publishers, content providers and other content-intensive businesses, to precisely identify and automatically tag multiple relevant entities, facts and events buried within large textual repositories. The process produces richly-tagged XML files. The output of ClearTags can be used to create new products and re-package content for various downstream applications and delivery methods, or for further analysis. ClearTags accepts input in a variety of formats, including PDF, MS Office, HTML, and XML, and automatically enriches each document with an extensive set of relevant meta-tags. The tags are based on three main technologies: Semantic/Linguistic Information Extraction, Statistical Categorization, and Topological Analysis. ClearTags is also used to generate a ClearForest knowledge base, to be used with ClearResearch, ClearForest’s enterprise research application, or third-party Web applications.