DOC-TAGS – Contextual, Accurate, Automatic Document Tagging
AI Machine Learning Approach Makes Doc-Tags a Truly Automatic Document Tagging Solution
DBI Technologies Inc., the award winning innovator of Interface Design, Scheduling and Text Analytic component software solutions, proudly announces the premier release of Doc-Tags. Doc-Tags is a software solution for automatically processing Microsoft Word (.docx) and Text (.txt) files of any subject matter into each file’s own list of contextually accurate document tags. The finished result places contextually accurate tags into the document’s own profile Tag Property, elevating the processed documents into accurately relevant searchable resources. Long lost content can now be turned into valuable resources automatically by surfacing a document’s key subject matter as key-phrase Tags making the content fully searchable by the file’s contextually accurate document description tags.
Doc-Tags is a software product that automatically creates a contextual list of accurate descriptive keywords and key-phrases (Tags) for any Microsoft Word (.docx) or text (.txt) file. Operating in any one of six international languages; English, French, German, Japanese, Korean and Spanish, Doc-Tags automatically generates lists of contextually accurate Tags (key words) for a document and adds them to the file’s Metadata – specifically the file’s Tag Property. A Doc-Tags processed document becomes immediately searchable by its new set of contextually accurate key-phrase tags.
Unlike other keyword software, DBI dispenses with an industry common practice of using referential list comparison strategies (Bayesian and Heuristics) using it’s own xAIgent service to deliver uncommon contextual accuracy in an automated structure that does not require subject domain specific training. Doc-Tags will take content of any subject matter (in any one of six supported languages) and automatically turn that content into a descending list of contextually accurate key-phrase Tags ranked from most relevant to least relevant.
xAIgent, found at the heart of Doc-Tags, is a patented machine learning and artificial intelligence-based key term extraction web service. In addition to automatically surfacing a document’s contextually accurate key-phrases (Tags), Doc-Tags also provides its users with a relational XML database, which keeps track of each document processed and the tags generated by document, giving the user incredibly useful relational reporting.
Document Tagging is a critical component of Document Management and Content Retrieval systems allowing for Accurate retrieval of content in perfect context of the subject of interest. Automatic Document Tagging works well with Content Management Systems (CMS), as well as localized implementations where Doc-Tags can process a hard drive load of documents turning unstructured content into contextually accurate, searchable information – digital gold.