The challenge was, in essence, semantic: teaching computers to decode complex product descriptions and isolate their essential attributes. For another client, Ghani, along with four Accenture colleagues and a Carnegie Mellon computer scientist, used a Web crawler to pull product names and descriptions from online clothes stores and built an algorithm that could assess products based on eight different attributes, including ?age group,? ?formality,? ?price point,? and ?degree of sportiness.? Once the products had been assigned values in each of those categories, they could be manipulated numerically?the same way that Ghani?s predictive models had tried to make sense of the grocery shopping list. By reducing it to its basic attributes?lightweight mesh nylon material, low profile sole, standard lacing system?a retailer could predict sales for shoes it had never sold before by comparing them to ones it had.
Source: http://feeds.slate.com/click.phdo?i=bc336b4e8a3e85b8a03705f7602b065b
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