Heuristic Boolean Patent Search Comparative Patent Search Quality / Cost Evaluation “superboolean” vs. Legacy Boolean Search Engines

This paper explores the application of an expert system to Boolean patent searching. Speci fically, it will introduce skilled researchers to the next technological evolution of search methodologies that apply Heuristic Boolean methods to reduce cost, increase efficiency, and enhance search results quality. Boolean search methodology, otherwise known as " keyword searching, " only extracts documents from a database that literally match the search query, but Boolean engines have no capability of determining which of those documents are of highest interest to the researcher. In an effort to overcome this limitation, modi fications to simple Boolean engines have emerged, including truncation, proximity searching, nested complex query capability, and wildcarding. But even with these enhancements, at best, Boolean searching remains little more than an iterative process of applying a query construct to a database in order to (a) extract a reasonable number of documents within (b) a reasonable amount of time, in order to (c) produce the most relevant documents supporting the search objective. At worst, the restrictive nature of Boolean search methods inordinately increase direct and indirect search costs, and establishes a false con fidence in search results quality that i ncrease exposure to long term legal and commercial risks. The patent documents that Boolean engines inherently miss, sometimes discovered years later by other researchers, often establish the true (high) costs attributable to Boolean searches. This paper examines how next generation Heuristic Boolean search methods can more quickly yield the most relevant documents, mitigate long-term risk associated with poor quality results, and reduce the direct, as well as hidden costs attributable to legacy keyword search engines. When the arti ficial intelligence of Heuristics is applied to Boolean patent searching, even novice researchers can quickly achieve reliable search results. A future invalidity search is the ultimate quality test of today's patentability search. Relying on the best search tools and processes today is critical. The future invalidity search performed when millions or 10s of millions of dollars are at risk, and can easily challenge and outperform the earlier patentability search because: 1) Liberal budgets for invalidity searches allow signi ficantly more investment in search labor (higher cost), and 2) Invalidity searches rely on search technology advancements which have evolved since completing the patentability search. The demands to perform a patent search that attempts to identify all of the relevant documents within the scope of available resources (time, budget, computing time, a given …