As an Intellectual Property Professional, it is important that your strategy is clear before the patent drafter begins to write the claims. There are many claims construction approaches to attaining exclusivity for your innovation either by a broad claim, a series of narrow claims or a combination of both. While your exact strategy makes a lot of difference to the way claims are constructed, an important consideration is the choice of words.

The choice of words that you make will aid not only in patentability of the applications but also, at a later stage, in freedom-to-operate and infringement. Experienced drafters know that it is important to avoid commonly used words in the domain of the invention.

One way that you can prepare a claims wording strategy is to create a set of closest prior art and using a text mining software, segment (tokenize) the claims. In case of patent drafting, it is best that you do not apply any taxonomy or thesaurus to fuse generated segments (or keywords) since you would like to see all popular variations.

For organizations, its advantageous to view these statistics in context of other companies in the same domain (using a Assignee-Keyword matrix). Interpretation made from these matrixes can help not only in the choice of words but also in your overall patenting strategy for your product.

For instance I segmented the claims and created a similar matrix in a search set for a drug (citalopram) in Patent iNSIGHT Pro Co-occurance Analyzer and exported that into a Patent Assignee-Keyword Matrix in Excel. While many different interpretations can be made from such a matrix, if your interest is to work around key claims then the spread of assignees around the keywords can greatly help your choice of words for the claims.

The matrix also helps in competitive intelligence. For instance a look at all the claim segments containing the words “disorder”, “phobia” or “syndrome” gives a clear indication of the applications areas that are being targeted by the companies.

So, while technology landscaping requires clustering the keyword segments into topics using various clustering algorithms, claims keyword analysis has many advantages for creating a patenting strategy.