SEARCH ENGINE OPTIMIZATION BY SELECTIVE INDEXING

摘要

Example embodiments involve a system and methods for identifying valuable view item pages for search engine optimization. The system and methods provide an improvement over existing systems, which do nothing to identify or select valuable view item pages for use in driving traffic from display sites. The system and methods described herein improve the earlier system by predicting the probability of future traffic for a given product based on a number of product level factors as input variables, and identifying a selection of view item pages corresponding to the products with the probability of the highest future traffic in order to maximize the driving natural search traffic to a linked site of the corresponding view item page.

主权项

1. A system comprising:
one or more processors; and a memory storing instructions that, when executed by at least one processor among the one or more processors, cause the system to perform operations comprising: collecting input variables from a database; the input variables including item level factors of a product; generating a machine learned model data object based on the input variables; assigning a target variable to the machine learned model data object; training the machine learned model data object based on the target variable and the input variables; calculating a natural search traffic probability of the product based on the trained machine learned model data object; and indexing the product based on the natural search traffic probability and the item level factors of the product.