TermSet is a metadata creation and tagging solution powered by machine learning.
It provides businesses with a full understanding of what information sits inside documents by using ground breaking technologies like Natural Language Processing and Machine Learning to effectively ‘read’ documents.
TermSet is well positioned to revolutionise search, governance and navigation resulting in huge savings of time and money.
By automatically adding accurate, consistent metadata and taxonomies Termset is likely to have a significant impact on the deployment of SharePoint solutions, especially where the focus is on knowledge or document management.
According to IDC over 80% of information is in unstructured content such as Office documents, PDFs and email.
TermSet uses natural language processing to generate taxonomies directly from the information contained within business documents. It automatically recognise many types of entity automatically, such as the names of people, company names, city, country, technical terms, and much more!
Tag documents from an existing taxonomy
TermSet can be linked to the taxonomies you already have in SharePoint and used for metadata tagging. It's intuitive engine understands the hierarchies, synonyms and multiple languages within taxonomies, searching and tagging them as it reads a document.
Real time tagging capability
As new documents are added to a SharePoint library TermSet will read them and automatically extract the metadata, preventing a manual exercise on each upload.
A great tool within TermSet to identify and extract fixed format values that your business uses such as parts numbers or project codes. This can then be added to documents as metadata.
Language analysis and tagging
An ideal element for worldwide businesses, TermSet can determine the language a specific document is written in an tag it appropriately, allowing for simple filter function to narrow searches.
Create document summaries
TermSet can generate a summary of a document in the language it's written in thus reducing time spent searching document libraries. The summary is created as a metatag to boost user productivity.