Patent Search Evolution : Manual Vs Automated Search
Patent Search Evolution : From Manual Labor to Robotic/Artificial intelligence Based : As the name signifies, the Manual Patent Search involved going to the public search room in the U.S. Patent and Trademark Office in Virginia to search manually through books of published patents. The search was done on the U.S. Patent classification Codes. The Patents gradually moved from books to micro-films and to CD-ROM with the method of search remaining same- classification code search, patent document retrieval, and patent reading. The chances of missing relevant patents were comparatively high with the patents not always being in the expected classifications.
Patent Search Evolution
The 90’s noted the computerization of the patent documents into a single database that could be accessed from the Web. Later, in 2006, Google Patents took this to the next level with simple keyword search anywhere in the patent document.
The method was not precise enough as ‘simple keywords’ can be many. Hence, the chances of missing patents were less but remained.
Multiple keyword searches, using Boolean Operators enabled faster searches with higher relevance. This was, however, the second age of patent search. Though helpful at a glance, this search method too had its disadvantages. It was not cost-effective and was time consuming.
With an exhaustive volume of patent data, automatic search can only be the solution to minimize human effort and keep from missing out any important details. Patent Analytics is the solution for this- these are built on an integrated database of patents, and include data corrections, patent transactions to see current owner, status updates, and often other information, like patent litigation, to see who is active in asserting patents. It allows the IP specialist to perform analysis quickly and accurately, directly addressing business questions. It also gives in-depth statistical analysis of patent activity in a particular technological area. It helps in translating large sets of patent data into a collective overview of analysis of a current market situation. The automated tools work faster with greater efficiency, minimizing possibility of error, giving a better view of current technologies and disruptive technologies, which can cause damage to any product.
Know More: Invalidity Searches by Sagacious IP
Artificial Intelligence (AI) based patent searches enable everyone to identify the most relevant technical literature quickly. The keyword is converted into an array of concepts, compared to a database of interrelated concepts. The artificial intelligence based search helps match the ideas, not the mere keywords thus streamlining the search. AI is progressing much with tools coming in, which are almost “at-par” with human intelligence. These AI based tools have the capability and knowledge of performing permutation and combination, applying logics on the patent data to derive insights, which might be difficult to formulate by a human researcher.
The evolution of Patent Search from manual to today’s AI based searches is unique. Searching over millions of data is now an easier and more dependable method with the help of automatic tools, which help in much time saving.