Balancing a comprehensive search against a targeted search, patent searchers can be quickly overwhelmed by large numbers of patents, no matter how careful the process is conducted. Network Patent Analysis (NPA™) can augment any patent search in a new and sophisticated way. One out of five among the most important patents would have not been found otherwise.
With more than 1.9 million new patent publications each year, the need for effective and efficient analytical tools to makes sense of this great source of competitive intelligence is increasing. A good understanding of the patent landscape for each subject matter is needed to make smart and strategic business decisions. Patent landscaping is increasingly recognised as a valuable business tool in the areas of research and development, patent and company valuation, patent litigation, and IP management.
Most commercial or public patent databases can be searched based on the likes of keywords, company affiliations, inventor names and International Patent Classification (IPC) patent codes. Balancing a comprehensive search against a targeted search, patent searchers can be quickly overwhelmed by large numbers of patents, no matter how careful the process is conducted. Searching by keywords alone can be flawed.
The use of different technical words by different applicants to describe the same concept may lead to partial coverage only. For example,‘petroleum’ can be interchanged with ‘oil’ in some circumstances. On the other hand a search term may be overcrowded. Within a relatively narrow field there may be many inventions, which can all be described with different combinations of the same technical words, but can be quite different solutions to common problems. A related issue is trying to determine the more important patents in a particular area, given the large number of patents often found. These problems can lead to force patent searchers, inventors, and patent attorneys to manually review patent documents. This can be time consuming, and even careful reviews can miss key disclosures.
THE USE OF NETWORK PATENT ANALYSIS TO AUGMENT PATENT SEARCH AND UNCOVER SUBJECT MATTER RELEVANT PATENTS AND TECHNOLOGIES
An alternative landscaping approach that overcomes the limitations of key word search or text-based data representation is to characterise patent disclosures and patent quality based on building a network of patent citations. The traditional patent search can be augmented by carefully considering not only the immediate search result, but also the inventions that are directly related via a patent citation. Patents need to be novel and inventive in relation to the prior art, and if not the applicant, then the patent examiners will always search patent databases to find the closest previous inventions to compare the patent application against. These ‘reverse’ or ‘backward’ citations are published by many patent offices, and many patent databases list these patent citations. Note, that non-patent citatio ns are also listed in many search reports. Some patent databases also publish forward citations. The US Patent Office (USPTO) is particularly diligent at finding prior art patents, and it is not unusual to find over a 100 backward or forward citations listed with some patents. This process is also boosted by US patent applicants being forced to disclose all prior art patents cited by other patent offices for related family patent applications.
Patent searcher sometimes search for related patents by following the direct forward or reverse citation links. Sometimes this analysis can include a second degree of connectedness by following the backward citations to their backward citations, and so on. If you imagine a patent to have 10 forward and backward citations on average, in the direct relation alone each patent can lead the practitioner to another 10 publications immediately. In a second, indirect step each patent can be related to another 100 patent documents, some of which may well be overlapping. It follows, that when reviewing the citations manually, the sheer number of patent citations can quickly overwhelm manual review.
An alternative approach is to use computer software to augment patent search by including all direct or even indirect data and agglomerate these data trees to form large networks of inter-related patents. This process is extremely comprehensive and will also pick up on very similar inventions carrying different keywords, which would have been overlooked otherwise. However the resulting patent seach result set can have tens of thousands of patents. While manual patent review will struggle with this many patents, NPA™ patent analysis will thrive, and may even benefit from the statistical robustness given by a large data set.