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More Patents Means More of A Need For Semantic Technology To Help Sift Through Them

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Did you know that more U.S. patents were granted last year than for any previous year in the past forty-odd years, with the exception of 2006? So reports Dr. Mark J. Perry, professor of economics and finance in the School of Management at the Flint campus of the University of Michigan, here. That added a heap of patents – near to some 200,000 – to an already full plate that organizations often have to dig into, whether to identify patent infringers, to sell off some IP, to improve their existing portfolios with additional IP from other sources, or even to explore whether one of their own innovations is worth patenting.

Just as those patent grants surged in 2009, TextWise introduced as part of its semantic similarity matching API a service to help businesses expedite U.S. patent searching. That semantic search capability now is included as part of Innography’s IP business intelligence system for managing, protecting and getting ROI out of patents.

The semantic service Innography has partnered up with aims at helping the general population of business users – not just high-priced expert patent searchers – get “more like this” matches to generate good results without having to run iterative searches, Textwise president Connie Kenneally explains.

“We have high precision and high recall – recall measures how well a search system finds what you want it to find, and precision measures how well it weeds out what you don’t want. We bring back really targeted finds that weed out the things that don’t really matter, and I’m not sure you find that claim anywhere else, certainly not in ‘more like this’ functionality.”

There are a handful of other players in the semantic patent search space, of course. That includes LexisNexis, which offers semantic search capability, enabled by PureDiscovery, in its TotalPatent service that helps researchers discover additional related concepts to consider in the course of their patent searching. “Others use semantic technology in different ways, for example, to rank results set or do clustering or metadata annotation,” says Kenneally of the competitive landscape. “From our perspective the primary thing we bring to the table is what we might refer to as one-click patent searching or effortless querying or queryless search,” she says of Textwise’s approach. “We don’t have to have people deconstruct information in order to pick out the right word in order to find the really highly relevant matches. They can just take a composite of text …and use that as a basis for matching.”

There are a few reasons why Kenneally thinks semantically-enabled patent search matters even more in these challenging economic times. As one example, it costs about $50,000 or $60,000 for the patent process, so universities, research hospitals and even companies more mindful of expenses these days may want to know whether they’ve really got something different, especially in a crowded space, before making that kind of investment or hiring a patent attorney to do some footwork.  At the same time, while “people are being more cautious about the kinds of things they patent, they’re also being aggressive about the things they do want to patent,” Kenneally says.”It’s a very vibrant market space now and with the addition of all these business people into the process, you need a lot more tools – such as semantic tools – to help them to get answers to their monetization questions quicker than in the past.”

It might also make it economically attractive to businesses to bring patent search efforts, many of which have been outsourced to India where expertise is high but cost of labor is low, back onshore, to be carried out by internal business staffers.  “When you look at where this play, if you can do it here economically and cut down on the work that has to be done by all these expert searchers that are expensive here in the U.S., it’s a huge opportunity,” she says.

The API and patent service still also will be available directly to Textwise clients who license it, which Kenneally expects primarily will be smaller companies that may not have a commercial platform in place. That includes small patent firms that don’t need the packaged solution’s features for themselves monetizing the results of their searches. They can still perform a certain number of queries per month with relevancy results for matched patents starting at about $12,000.

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