Assignee names in AcclaimIP are normalized.  This means that you can search on one version of a company name such has "IBM" and you'll get an inclusive search including 655 different versions of their name found in the patent database.

It is almost impossible to make sense of patent data if names are not normalized.

This is one of the more complex "fields" in patent searching.  AcclaimIP uses a total of nine (9) assignee name fields to keep everything straight and also give you the power you need to efficiently search assignee names.  This article is designed to give you a quick start.  More details on Assignee Name searching can be found in our Advanced Syntax section.

When patents are examined in patent offices around the world a special group of patent classifiers as well as the examiners classify the patents.  They do a remarkable job in my opinion.  Classification searching is the best, and really only way, to do a credible job of isolating technologies for patent landscapes and comparing two portfolios without doing extensive manual classification yourself.  I'll just say it, a lot of patent search professionals don't trust, don't like and rarely use classification searching.  While I think it is a big mistake, I understand it.  Classification analysis is not handled well in other tools that I have seen.

Clearly, all patents are not classified perfectly, and some patents aren't classified at all and dumped into catch-all classes, such as the 1/1 class in the US Classification system.  But with the vagaries of human language it is your best bet.

AcclaimIP handles classification in very powerful ways as will be explained in this and other chapters of the Help Manual.

When searching for patents, it is important to pick the best keywords that will select for the patents you want to find.  The terms found in these patents may not be obvious, so you'll have to go through an iterative process to identify key terms found in patents you want to isolate.  For these reasons, AcclaimIP includes several powerful tools to help you analyze patent keywords which are discussed later in this chapter.

What do patents read on?

You'll find that the vast majority of patents don't read on devices or products such as endoscopes, mobile phones, laser printers or light bulbs per se.  In general, patents also don't even read on components of devices such as touch screens, microprocessors, cameras and fusers, but rather they tend to read on features of components of devices.  This distinction is important because you will likely get better more targeted results if you focus on a single feature at a time.

A good search strategy will focus keywords at the feature level or possibly the component level, and not on the device level.  AcclaimIP provides a multi-tier matrix query feature which will help you roll-up your feature and component level queries to the device or even product class level.

The Keyword Analyzer tool counts the term frequency of specific terms found in a single patent. It is found in the "Keywords" tab on the document details window. Depending on how wide you set your DD window, you may have to scroll to the right a bit to expose the Keywords tab.

The Keyword Analyzer uses a straight term and string count method. It breaks up the terms counted in the document into two sets, the Claims Only and the Full Text.

The Keyword Analyzer uses stop-terms to remove common words like articles and prepositions, as well as common "patentese" terms like method, apparatus, claim, invention etc.

The Keyword Analyzer has a tool for creating new queries from the terms found in the patent of interest.