Automated classification and taxonomy generation software are similar types of software but create a different level of results. The difference between the two types of software is the depth of their uses. Automated classification systems will assign index terms and metadata, whilst automated taxonomy generation creates categories and taxonomies. These tools automatically produce index and metadata classifications, or organise content hierarchically respectively, to help information architects deal with large levels of information in digital spaces. Kat Hagedorn describes this as the saviour of information architects struggling with the vast array of content constantly being created on the internet and intranets (Hagedorn, 2001, p. 3). These tools are intended to help information architects deal with the constant influx of new materials which reports state that 90% of new business records are created digitally, and 40% of those will never be printed (Cisco & Jackson, 2005, p. 45) so this requires a framework that will help, not hinder, the majority of making those records organised and tagged appropriately.

There are different approaches available to information architects using these tools and it inevitably comes down to the involvement that information architect would like between manual use and automation. Peter Moreville and Hagedorn both suggest that human involvement is necessary (Moreville, 2000; Hagedorn, 2001), because without it automated systems would repeat mistakes over and over. The amount of human involvement comes down to the algorithms that define an item to be categorised a certain way, or developing the rules if an algorithm is not used, and a process of reviewing and testing to keep a level of quality control. For such a system to work at a high level it is worthwhile to invest in keeping and maintaining a controlled vocabulary, which is going to have defined alternatives and terms that don’t allow the automated systems to categorise content into superfluous terms. 

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