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Recent blog posts

Flextronics AP LLC has in recent years developed a portfolio of patents for connected cars. This includes 79 patent families including 11 patents.

In the blog found here, patent analyst Dr Alex Lee of TechIPM (Boston) reviews these patents and uses the LIcensing Potential metric developed by Ambercite to identify the companies that Flextronics may  be able to licence their patents to. This list is headed by Cisco and AT&T.

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Who has the best portfolio of patents for smartphone patents Near Field Communication - and who might they license to?

These are questions asked by patent analyst Dr Alex Lee of TechIPM, of Boston. Dr Lee has combined his detailed knowledge of this area along with the Licensing Potential analysis developed by Ambercite to write the blog titled NFC Patents for Smartphone Mobile Payments Licensing Potential Assessment

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Demand for inter parte reviews IPRs has been three times higher than the USPTO expected, with 3,277 IPR reviews filed in the last 3 years. This was according to a recent blog published by the director of the USPTO. The director also pointed out that to date only 12 % of claims, to be challenged in the contested patents (4,496 out of 38,462), have been invalidated in a written decision. Other claims were either not challenged, cancelled, resolved by settlement or upheld. This is a interesting contrast to the sometimes held view of the PTAB as a 'patent death squad'.

The 12% ‘success rate’ suggests that the IPR process is far from a walkover. The IPR process allows the petitioner to submit either new or known prior art. Known (or previously cited) prior art is easy to find, but in some cases this can involve reviewing a long lists of prior art citations.

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We have had some questions recently from the likes of universities and even some companies about why they should look in the patent literature when assessing inventions,  when they could look in the scientific literature instead.

To me this is a false dichotomy – ideally a diligent searcher would look at both. But putting this aside – how do they compare? To help answer this question, I have prepared the table below:

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Verve has just reported that Segway, maker of the Human Transporter

 

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Most people reading this have an interest in patent searching. I remember the first time, working as a development engineer, I was asked to search the patent literature. This was a long time before the advent of readily available online searching, and so I found myself reading through a printed collection of relevant patents. I was fascinated that this vast collection of information was available to me, and many years later I still am.

Nonetheless, all of us have clients or managers and need to justify what we do. So how can we justify the cost of a patent search?

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I think all of us would admit that we are not 100% perfect patent searchers.  We may be very strong in some areas, but are unlikely to be perfect across every technical area we are asked to search in. 

Also keyword searching, even under the best of searchers, can still have its limitations as discussed in an earlier blog.  

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A question we often get is 'How does Cluster Searching work?"  

Without giving away too much of the propriatory details, Cluster Searching uses citation links to identify similar patents, Once people know this, they often ask something along the lines 'does this use keyword matching as well?

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We speak to people all around the world about our Cluster Searching patent searching tool, and one of the most common questions is "how does this differ from conventional citation searching?" This is an excellent question. 

To show you the differences, consider US patent US6898550, filed by Fitsense Technology and now owned by Nike, for a Monitoring activity of a user in locomotion on foot. This claims a method for predicting fitness based the direct measurement of foot strides.  

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Licensing managers are often called upon to identify potential licensing options for portfolios of patent they might manage. There are a variety of ways of doing this, but perhaps the easiest way, and a very simple starting point, is to start with the patents themselves.  

Ambercite has recently developed Cluster Searching, which is a web application for finding the most similar patents to one or more starting patents. This is done using advanced analytics which are applied to patent citations. Each patent citation is an opinion by an expert (being the patent applicant or examiner) that two patents are similar. The advanced analytics within Cluster Searching then combine these opinions to work out which clusters of patents are most similar to the starting patents, irrespective of the keywords or patent class codes that are use. Date filters can also be applied to focus the search. The search can take seconds to run working from the patent numbers themselves.

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