Coining Phrases - Reverse Auto-Classification

Recently, I have been talking with some software folks who have created parsers for auto-classification. These engines will take a text or website, scan the contents and see how it matches to a given taxonomy. These parsers use a variety of techniques including statistics, semantics, word location to see how a given document matches a taxonomy. These are very impressive, and I hope to use one of these for our taxonomy to classify our content. One of the unique traits of our taxonomy is that is multidimensional, and we use those dimensions to show the different ways that businesses operate in our economy. We have been able to leverage this to find buyers, sellers and comparables for Mergers and Acquisitions. One of the problems with this approach is that users who are searching our database need to have a fairly in depth knowledge of the taxonomy in order to find what they need. To solve this problem, we decided we needed to create meta-terms or coined phrases that would represent different search criteria to apply to our taxonomy. Instead of, going from text to taxonomy we are going from taxonomy to text. We also use all the synonyms for all the nodes in our taxonomy. So instead of having users select their criteria from a series of drop-down boxes, they can type in a Google-like text box and the software will auto-fill matches against the table of coined phrases generated from our taxonomy.

I have a live sample on our MandAsoft site here: http://mandasoft.com/segments/searchlob.aspx. A good example is accountant software which is a coined phrase that will search for software for accountants. Here are the results for that search http://mandasoft.com/segmentview.aspx?SearchID=LOB99.
Tell me what you think.

Why is a multi-dimensional faceted taxonomy better for Business?

As we have seen, we can more closely describe a company and how they operate by using four different hierarchical trees to categorize their clientele, their methodologies, their solutions and their channels. This faceted taxonomy definitely gives us a better view of any particular business, but at what cost.  Our team has definitely found using this taxonomy has been challenging to categorize a given company. The taxonomist must research thoroughly a given business, and then be able to abstract that understanding into the four different dimensions. Another challenge we found in our first search tool, was that the user using the search tool needed to understand how to abstract the kinds of businesses they were looking for into the four different dimensions. These two issues makes us wonder whether it is worth it. (Currently, we are working on software algorithms to make the search more user friendly and to make suggestions from web scraping to help the categorization.) 


We find it is worth it. The reason why is that, unlike NAICS codes, our taxonomy allows us to dig into micro-market views. NAICS is good for broad markets, but not for close views of a given market segment. Looking back to the 2004 Presidential Election, we see that President Bush's team was able to efficiently direct resources by using Microtargeting. The impetus of our taxonomy is Mergers & Acquisitions, and an important part of that process is valuation. To find the potential target company of an acquisition, investment bankers search for recent comparable deals. A task that is impossible using NAICS codes.  With our taxonomy, we can do this. The reason is because we have moved away from the traditional way of viewing "Business" which is in terms of a vocabulary.  Instead, we now can view "Business" as a multi-dimensional space where we can define "Spheres of Competition" to determine "comparables". Stay tuned for more.