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.

The QueryFlow tool differs from the Keyword Analyzer in several ways:

• QueryFlow uses a powerful algorithm called TF/IDF (Term Frequency/Inverse Document Frequency) to find "important" terms in the source document.
• QueryFlow defaults to a Boolean OR operator compared to the Boolean AND in the Keyword Tool.
• Terms are weighted using Query Flow.

An "important" term is defined as a term that appears in the patent with a high frequency but does not appear very often in the entire patent corpus.  As a result, TF/IDF doesn't need stop terms.  Terms like the, and, but, with etc appear so often in the corpus that they are never identified as "important" terms.  Even "patentese" terms such as method, apparatus, system appear so frequently in patent data that the algorithm never deems them "important."

Because of the weighting, and the nature of the Boolean OR operator, QueryFlow does a much better job of creating inclusive lists.  But the list can be very large.  The most relevant patents will be displayed at the top of the search result list.

Term weighting boosts a term's relevance in the search results and increases the overall precision of your query.  Patents with higher weighted terms appear higher in the search results.  Weighting terms does NOT impact the recall, which means the same number of documents will be returned by the search engine no matter what weighting you use.  But the order in which they appear will be affected.

AcclaimIP has up to 40 columns of data which you can expose in your search results. Depending on the type of search you are doing, you will want to show different column sets by default. You set your defaults in your Preferences.

However, very often, you may want to add a new column on the fly without having to update your Preferences and redo your search. This is really easy to do in AcclaimIP.

In this article, we'll review some of the basic ideas behind keyword searching.  

Patent documents are full of words.  Patents themselves can be relatively short, such as a two page design patent, while other patents can contain over 1000 pages of text!

Keywords are mainly found in four fields: Title, abstract, claims, and specification (which is also called the description or the disclosure).  When keyword searching, you'll want to keep in mind where in the document you want to search for certain terms, and how the language might vary in different parts of the document.

A keyword can be either a single term, like "fingerprint," "security," or "financial."  A keyword can also be a string such as "light emitting diode," "wireless communication" or "target molecule."

Too often patent searchers rely too heavily on keyword searching.  Keyword searching is amazingly powerful, but it should be used in conjunction with classification, and date searching for optimal results.