The Linear Law of Patent Analysis was proposed as a framework for performing patent analysis projects in 2002. It was developed to assist practitioners in understanding the importance of starting an analysis by investigating the needs of the customer for the analytics, as opposed to simply jumping in with an analysis tool. A brief overview of this concept and methodology for performing patent analytics will be discussed.
Due to the nuances of the worldwide patent system a situation exists where a single invention might have many individual patent documents associated with it, depending on the number of countries the applicant sought protection in. The situation becomes even more complicated as patent documents are published at different stages throughout the prosecution cycle. In order to clarify the number of inventions produced compared to the number of patent documents published, the concept of a patent family was created. There are a number of different types of patent families, and methods for reducing the number of documents to represent a family. An examination of these different methods will be provided.
Data cleanup and grouping are processes for the manual, or automatic standardization of terms or items, within a data field, to correct errors or inconsistencies, or to group synonymous entries. It is required by patent analysts in order to produce statistically relevant results. It is necessary since raw patent data is notoriously "messy" and requires cleanup or standardization to produce accurate results. Misspellings, for instance, are a common occurrence within certain fields, and require correction. There are also many terms with the same or similar meanings, within the English language, and these should be grouped together when analyzing concepts. Specific examples and tools for cleaning and standardizing patent data for generating a data table will be covered.
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