Trademark applications streamlined by machine learning
Advanced machine learning technology that will assist in streamlining trademark applications is being implemented at IP Australia.
Designed and built by IP Australia, the Smart Assessment Toolkit utilises historical datasets to provide valuable business insights and streamlines the examination process by using machine learning models to quickly identify potential issues and alert trademark examiners to them.
The initial toolkit includes:
- Smart search — automatically comparing new plain word trademark applications with earlier registered trademarks to produce a list of hits based on similarities of goods and services.
- Word analysis — analysing a plain word trademark to identify and match problematic terms. This includes potentially objectionable issues such as scandalous matter, geographical locations, common names, plant names, laudatory terms and single characters.
- Ownership — retrieves and analyses ownership information against other data such as the Australian Securities and Investments Commission (ASIC).
The toolkit enables a smarter way of working and is the result of IP Australia’s continued utilisation of cognitive computing technology, which was also responsible for the successful launch of Trade Mark Assist on 2 May 2018.
“This is a game changer for trademark examiners. We’re embracing advanced machine learning technology to provide leading-edge tools to our staff and improve our service to customers. This technology helps examiners focus on more complex and value-added tasks, allowing better use of our skilled staff and improved quality of administration,” said Patricia Kelly, Director General, IP Australia.
The Smart Assessment Toolkit initiative is about providing decision support within the examination process as part of IP Australia’s ongoing commitment to quality.
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