The problem

Usually IP search filters are designed quite broadly to assure no relevant hits might be missed. As a consequence however, the search result contains a considerable amount of non-relevant IP also ("noise"), which can be up to 80% of the total result or even more. This is where infoPatent Classifier comes to your help.

 

 

The solution: Automatic relevance test

infoPatent Classifier is a self-learning system based on latest text mining technology, fully trained and specialized on treating with IPR documents.

infoPatent Classifier now uses the contents of one directory as a reference (learning set) to determine whether an incoming IPR shall be considered relevant or "noise".

This is done completely automatically: the result is presented to the user in a well-structured manner, and the user can decide whether to accept the relevance proposal of the Classifier in parts or in total, or not.

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To experience the power of infoPatent, please contact help(at)infoapps.de and help yourself to a time-limited trial access to infoPatent at no charge and obligation.

infoPatent is especially designed for:

  • Developers (reading and feedback)
  • R&D Managers
  • Patent Specialists
  • Patent Departments

infoPatent offers these benefits:

  • Worldwide coverage - always up-to-date
  • Family consolidation
  • Inclusion of figures
  • Semantic searching algorithms

Contact
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