Are you still searching like it is 1998?

Nokia phone 1998.jpg

Remember 1998? When the most popular selling 'smartphone' was this Nokia?

 

 

 

 


  Espacenet query window from 1999 - the earliest Espacenet image I could find.

Espacenet query window from 1999 - the earliest Espacenet image I could find.

1998 - the year that online patent searching become available.

1998 was actually quite a year in the development of patent searching. Espacenet was introduced, and caused quite a stir as the first free and internet based patent search engine.  And it was very useful - you could run a patent search by entering a set of keywords and other criteria, and it would return all patents that met this criteria, for example:

Show me a list of patents filed by Toyota and including the words "hybrid car" in either the title or abstract. In other words, filter out the patents that do not meet this criteria.

Compared to paper based patent searching, this was a big step forward, although Keyword searching for patents was not a new concept. Derwent hds offered, via mainframe access, access to keyword searching for many decades, even if via subscriptions that even back in 2001 could exceed $100,000 per year.

And you will recognise today that this concept of 'filter searching' is still widely used. 

So 1998 was a great year for patent searching. But there was a second development that we might have missed at the time, but which has also had a bit impact on patent searching. 

 

 

 

The other big searching advance in 1998

But also in 1998 come another product launch that over time has had even a bigger effect on what we do. But before we do so, it is worthwhile considering what general searching on the internet was like back in  1998.

20 years ago, searching the internet meant often visiting the likes of the Yahoo web portal. There you would be presented with an early classification system for the internet. There were various classifications, and the ability search for web pages that included target keywords.

March 1997.gif

The front page of Yahoo looked like this (only a partial list of the available topics are shown to the right)

 

 

 

 

 

 

 

 

 

Yahoo search March 1997.gif

And yes there was a word search function:

20 years ago, we thought that was hot stuff - the ability to filter websites by keywords.

 

 

 

 

 

 

 


Google beta.gif

But in 1998, this webiste appeared:

Google was based on the PageRank algorithm, which was an Artificial Intelligence (AI) approach to searching webpages, named after Google founder Larry Page. Rather than just relying on page filtering, the PageRank tired to predict what you wanted to find, based on, at that stage, connectness between websites. By all accounts Google has developed its secret sauce algorithms a long way since then, but the key breakthrough still stands - that there are smarter ways of searching than keyword filtering.

But does this apply in patent searching?

 


 

 

Have we moved beyond keyword and class code filtering in patent searching?

First of all, I fully admit that there remains a place for traditional filter-based keyword and class code searching.  However, just like the world of web searching has provided other options, so has patent searching. 

Like Google searching for websites, AI based patent searching can quickly and 'magically' find you relevant websites, using principles more evolved than keyword filtering. AI algorithms include those based on:

  • Semantic analysis - where algorithms looking for similar language in other documents. In some versions of this, dictionaries of synonmums are used to broaden the search

  • Variations of the above using class code information

  • Other undicclosed algorithms

  • Citation analysis - which is what Ambercite AI is based. Ambercite thinks that citation can give more precise results as it is less dependant on particular keywords or class codes in the patents being found - 'a rose is a rose by any other name'. Ambercite has benchmarked Ambercite Ai against other semantic engines, and found very high relevancy rates.

In in most cases AI approaches are designed to be very simple to use, and to be used alongside traditional searching methods - because no one technique may give you the perfect results. And they can be very cost-effective because they can produce a list of results in a efficiently ranked series of results. 

 

Resistance to AI searching

Plenty of professional patent searchers are using AI patent searching as part of their set of tools, including Ambercite AI, but occasionally we speak to some who are reluctant to use these tools, instead sticking to conventional filter based searching.   Stated reasons for this including:

  1. Searching by keywords and class code filtering is the way that things 'have always been done around here'. 'It is the safe approach', and easy to describe to clients.

  2. While searching for patents using the conventional method can be time intensive, we have plenty of time in our organisation, so what does it matter?

  3. AI searching can involve 'black box' methods, and we should not use black box approaches.

  4. What is wrong with searching by keyword filtering in any case?

But how well do these arguments hold up? In response:

  1. The purpose of patent searching is to find relevant patents, and not to run a patent search process the way it has always been run. By using a range of methods including AI patent searching, you can increase your change of finding relevant patents, and so meet your purpose - and improve the quality of your search.

  2. In reality, all of us are under time and cost constraints. Our clients and managers want the best possible results at the least possible cost.

  3. Whether we admit it or not, we use black box methods to search online all of the time. Not just Google, but the likes of Amazon, AirBnb and Ebay all use black box algorithms to provide a list of ranked options for you to peruse, when you use them to run a search of some sort.

  4. Searching by keyword/class code filtering can work well in some cases. In other cases you will miss relevant patents with unexpected keywords or class codes. Because it bring up lots of low relevance patents to look through, it can be very time conusming to go through them all. In any case, the world is moving onto smarter tools - just like the world moved on from Yahoo to Google searching on the internet .

So the answer to the question "Have we moved beyond keyword and class code filtering in patent searching?" is yes! - Many searchers are incorporating AI search techniques into their search processes, through a variety of search processes.  And the others? - They are are still defining a high quality search using principles that not changed much since 1998 - back in the days when Nokia was king of the 'smartphones'.

 

Are you looking to move your searching beyond what you could do in 1998?

Contact us for an informative demonstration of our premier AI search tool Amberite AI  - or sign-up online to use our trial version (some limitations apply in the trial version). Discover why some of the world's leading patent owners and analysts use Ambercite to strengthen the quality of their patent searches.

 

 

 
Mike Lloyd