New Logo, New Look As you may know, Anaqua acquired AcclaimIP in late March of 2016. The entire team moved over to Anaqua, and since then we’ve more than doubled our numbers. We also purchased 40 full text English translated…
New Logo, New Look As you may know, Anaqua acquired AcclaimIP in late March of 2016. The entire team moved over to Anaqua, and since then we’ve more than doubled our numbers. We also purchased 40 full text English translated…
Natural language searching is a form of query by example or QBE, where you submit a block of source text, then ask the search engine to find documents similar to the example. Rather that returning a short list of very targeted patents, natural language…
We are happy to announce a new reporting capability in AcclaimIP. A report is a document that analyzes a patent or a set of documents from multiple perspectives. The first report we have built is the Patent Assignee Report, which…
The short video course is designed to make you a faster, more confident patent researcher. Four videos cover the fundamentals of patent searching using advanced query syntax. Most of the skills you’ll need to develop multi-faceted queries searching multiple parts…
The number of US patent documents published flattened out in 2015 after almost a decade of steady growth. The chart below shows total patent documents published in the US, which includes both patents and applications. At 709,453 total documents published, 2015…
One of the most powerful visualization tools in AcclaimIP is something we call multi-series charting. With it, you can create comparative analyses between two or more different sets of patents by making simple modifications to your queries and charting them together across…
One-click patent landscapes are now available for all users with the Analyst plan. Our landscapes blaze a trail by taking a completely unique, and ironically more standardized approach to creating patent landscapes. Not only are they amazingly accurate, but they are…
You might be surprised to learn how inconsistent agent (AGT) data is in raw patent records. Large law firms file patents on behalf of their clients using, in some cases, hundreds of variants of their name, and even small firms…
So you developed an excellent query and have limited your search results to a reasonable set of patents. Now its time to start reading the patents and evaluating the patent claims.
In what order should you start your analysis? You probably already know how to sort your results by the important value indicators, but did you also know you can sort your list by the relevance to a document or any block of descriptive text?
Take a moment to watch this video to learn how natural language searching can order your search results.
Why learn the technique:
Steps:
I don’t show it in the video, but you can use the Natural Language tab in the main Search window to order your search results based on any block of relevant text such as sample claims, an invention disclosure, or the relevant part of an industry standard.
The process is easy, saves time and keeps you focused on the most relevant patents
–Matt Troyer
While there are various types of patent searches, all of them have something in common – you are looking for result(s) that read on some IP document (invention disclosure, application, patent or set of patents and their claims). While conceptually a…