The number of patents has been increasing,[1] encouraging companies to consider intellectual property as a part of their strategy.
Software dedicated to patent visualisation began to appear in 2000, for example Aureka from Aurigin (now owned by Thomson Reuters).
Software converts patents into infographics or maps, to allow the analyst to "get insight into the data" and draw conclusions.
[citation needed] Patents contain structured data (like publication numbers) and unstructured text (like title, abstract, claims and visual info).
[10] The main step in processing structured information is data-mining,[11] which emerged in the late 1980s.
Data mining allows study of filing patterns of competitors and locates main patent filers within a specific area of technology.
This approach can be helpful to monitor competitors' environments, moves and innovation trends and gives a macro view of a technology status.
[14][15] This technique is widely used on the Internet, it has had success in bioinformatics and now in the intellectual property environment.
[17] An algorithm extracts words and expressions from title, summary and claims and gathers them by declension.
Four text parts can be processed with text-mining : Software offer different combinations but title, abstract and claim are generally the most used, providing a good balance between interferences and relevancy.
For instance, if a query produces irrelevant documents, a multi-level clustering hierarchy identifies them in order to delete them and refine the search.
[citation needed] Allying patent analysis and informatic tools offers an overview of the environment through value-added visualisations.