Cluster Searching


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Find game-changing patents missed by other tools

  • Simply input a starting list of relevant patents - any family member will do
  • Results are delivered in seconds and ranked by similarity for easy review
  • Great for patentability, novelty, examination or licensing searching - and so easy to use, it can be used at the start and finish of every patent search






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Explore the patent landscape

  • Understand how patents cluster together over similar claims.
  • Discover unusual ways of describing prior art.
  • Similarity and patent scoring let you prioritize.
  • Potential infringements are clearly highlighted.
  • Systematically work your way through the patent landscape



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Finds you patents missed by other search tools - quickly and easily

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Strengthen your keyword (or class code) searching with Cluster Searching

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Here at Ambercite we often talk about the limitations of keyword searching - but in fact we are happy to acknowledge that both conventional and Cluster Searching can be helpful in finding relevant patents - as suggested by the image below: 



And most of our clients do in fact combine conventional and Cluster Searching.

The good thing is that when our clients do use both forms of searching, the results from one can help support the other. For example, the best patents found using conventional searching can provide the starting patents for a Cluster Searching.

Conversely, Cluster Searching can help traditional searching with what can be a big issue for keyword searching - namely - "what keywords should I use in my search?"

What do we mean by this? Lets say, hypothetically, we were asked to invalidate US7,448,703 for a Retaining and adjustment device for movable furniture parts



This is a relative simple concept, and you might expect the search terms to be straight forward. 

Or maybe not? Lets think about this - what terms would you use to describe this invention? Furniture maybe? But would all similar patents use this term?

Anyway, while you are doing this mental exercise, we might show you the easy way, namely to plug this patent into Cluster Searching and run a search for the most predicted to be similar patents:



Which produces a whole long list of results - with a range of titles (only the top 12 patents are shown in this representative list)


From which, some more keywords become apparent:

  • door
  • flap
  • lifting
  • actuating 

And there are many more terms used if we were to keep on going down through the list.

There are a lot of very skilled patent searchers out there, and it is entirely possible that many of these searchers could come with all of the necessary keywords without using a short cut such as Cluster Searching to assist them. However I would suggest fewer of these searchers could repeatedly come with such a high quality list for every search they do - and in a few seconds.  

And of course, you could use the results shown as part of your patent search process.


What about class code searching?

What currently Ambercite does not display patent class codes in the results table, by clicking through* the top ranked patents you can quickly start to see which class codes are dominant - and this can help you make selections about which class codes to use in your conventional searching. 

* Each round blue button immediately after the patent number open up further details of each patent


And the net effect?

In our previous blog, we talked about Cluster Searching as being a form of insurance to conventional searching.  We still believe that this is the case - with an added benefit being that you can strengthen your conventional searching, using the added insight gained from spending a few seconds running a Cluster Search. 

This is suggested in the revised image below:





PS - Are you ready for your assumptions to be challenged?

One likely outcome of the using Cluster Searching to look for potential keywords or class codes is that your assumptions about the best keywords or class codes may be challenged. Luckily, the users of Cluster Searching are the sort of people whom are willing to challenge their own assumptions - in order to produce better results for their clients and employers. 


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Mike first developed an interest in patent data when working as a research scientist, and deepened this interest when working as an IP manager which led to his role at Griffith Hack. Mike has published in the areas of chemical engineering, patent management, the value of patents and the use of patent data in in a wide range of publications and forums, including the international journals Les Nouvelles, and Managing Intellectual Property.

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