Reading equities in join

We want a uniform presentation of a summary balance sheet for some variety of financial descriptions. Our search graph is just that, the definition of the normal form balance sheet and cash flow. Company financial information may be a bit scattered, but join learns the company, it sniffs through company text and develops key word list that help it organize financials. So we have new text, unseen from the company. We let join sift through it using is collection of categorized word lists. Do this fast, I mean fast; bring all the world list, reat4 them automatically. It can do feature detection if the feature hierarchy can be seen as directed graph, from general to specific. Feateurs mayber ber bit maps, match is adptd to find partial matches. Search for one or more close matches to known graphs. Math geeks know about which I speak. Handwriting analysis, finger print, image detection. The ability to stem roll though stacked layers of lists makes it work. Anyplace you have big data, treat is as set classification by learning, and keep the hierarchy of canonical sets developed by learning. This machine is thinking.