Try Amberscope now
Subscribe to Amberscope
Each dot on an NPA™ patent landscape map refers to a highly ranked patent, due to its strong connections with other patents. A larger dot indicates a more dominant patent, while a thicker line indicates a stronger citation relationship between patents. Clusters of closely located patents are more likely to disclose similar technologies.
Dominant patents are more and better connected to other patents, in a similar way as to how influential people are more connected to other people, many of them influential themselves. Highly ranked patents are more likely to disclose inventions of high value than lower ranked patents.
A cluster of similar patents suggests an area of high commercial value. Inventions cost money to develop, and patents cost money to file. A large patent cluster implies an important problem to be solved, which is likely to be commercially valuable.
NPA patent maps can be produced with a small identifying code next to each dot. This code can be used to find the details of this patent in the accompanying spreadsheet. Similarly, patents listed in the spreadsheet can be found in the patent map by looking for the identifying code.
‘White spaces' can be easily identified as the white spaces between clusters of patents. The potential subject matter of these white spaces can be estimated by considering the subject matter of the adjacent clusters. In addition, any unclustered patents that fall within the white space can provide valuable information about innovation opportunities.
Individual patent citations can be unreliable. However errors in individual patent citations should be randomly distributed, and so cancel out if enough citation data is collected. Up to one million citation linkages can be used to create an individual NPA analysis, well and truly removing the effect of individual error. Also NPA™ patent analysis looks for supporting data to confirm individual patent citation records,
NPA uses sophisticated and proprietary algorithms to combine and augment patent data collected from a patent search, and then identifies the patents with the strongest connections to other patents, and the strengths of these connections.
The majority of the earlier style patent landscape maps are created by grouping patents based on keywords. Grouping patents by keywords has no inherent ability to rank patents. Analysing patents by keyword also has a lesser ability to distinguish patents in a narrow technology field that can disclose quite separate inventions but use very similar keywords. Besides distinguishing patents using similar keywords that disclose different inventions, NPA™ patent analysis can even group patents that use different keywords.
The ranking of a patent in an NPA analysis is not only dependant on its citations, but also on the citation linkages of the patents it is connected to. A patent with a relatively low number of citations can still end up highly ranked by NPA, if it is connected to other highly ranked patents.
Because the ranking of a patent can depend on its related patents, even quite recent patents, granted within the last year or two and containing no forward citation data, can end up highly rated by NPA.
NPA is technology neutral. Providing that the key developments in a technology field are protected by patent applications, NPA will work with that technology.
NPA can combine the scores of individual patents to estimate and rank the quality of a patent portfolio and its owner.
NPA patent analysis is an objective means of combining the subjective opinions expressed within patent application and citations. The power of combining individual subjective opinions to rank items should be familar to anyone who has ever used a search engine or a social media website to look for highly ranked items.
Patent analysts are increasing recognising the value of patent citations, and some are developing systems can show simple citations relationships between patents. However NPA is more than the process of drawing citation relationships between patents. NPA™ patent analyis uses statistically robust quantities of patent citations to identify the leading patents and citation relationships. By our extensive analysis process we can:
Don’t be fooled into thinking a simple citation analysis and a pretty picture will suffice. At Ambercite we believe that patent landscape maps need to be robust and defensible, just like your business.
Ambercite and its products including Network Patent Analysis (NPA) and AmberScope analyse patent data using a statistical based approach that is based on available patent citation and ownership data. These outputs are purely mathematical in nature, and do not take into account the personal or professional opinions of any individuals or associates of Ambercite. These outputs are intended to be used as tool to help support further analysis, and should not be used by itself and without professional advice on the relevancy of this data to your unique circumstances. Data should not be relied upon to prove without any further analysis any opinion of the value, patentability, validity, freedom to operate or infringement of any patent, patents or inventions. Users should also be aware that available patent citation data is imperfect, and this will affect the results of this analysis. © Patent Analytics Holding Pty Ltd. Ambercite™, Network Patent Analysis™, NPA™ and Next Generation Patent mapping™ are trade marks of Patent Analytics Holding Pty Ltd. Components of the processes used to perform Network Patent Analysis and AmberScope are the subject of patent applications filed in the United States and elsewhere.