Abstract: 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.

Abstract: 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.

Abstract: Example embodiments involve a system and methods for identifying valuable view item pages for search engine optimization. According to certain embodiments, the system performs operations that include 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.

Abstract: Example embodiments involve a system and methods for identifying valuable view item pages for search engine optimization. According to certain embodiments, the system performs operations that include 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.

Abstract: Example embodiments involve a system and methods for identifying valuable view item pages for search engine optimization. According to certain embodiments, the system performs operations that include 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.

Abstract: Example embodiments described herein disclose a specially configured device to generate and cause display of human readable titles for browse pages. The token based title system may be or include a group of one or more server machines. A user device may accordingly receive a search query and set of structured data elements (e.g., filter attributes), create a browse node based on the content of the search query and the structured data elements, access published content (e.g., an item inventory) based on the browse node, and generate a human readable page title to be displayed as a title of a browse page.

Abstract: In various example embodiments, a system and method for generating a concept graph are presented. Trending queries are determined from a query log stored in a database. Item pages that correspond to the trending queries are identified. Aspects from the item pages are also identified. The aspects from the item page may be stored as pre-defined data within the database. Query nodes for each of the trending queries are generated, and the query nodes are included in a graph. Leaf nodes for each of the aspects are generated. Connections between the leaf nodes and the query nodes are generated. A destination page that includes various aspects is generated.

Abstract: In various example embodiments, a system and method for generating a concept graph are presented. Trending queries are determined from a query log stored in a database. Item pages that correspond to the trending queries are identified. Aspects from the item pages are also identified. The aspects from the item page may be stored as pre-defined data within the database. Query nodes for each of the trending queries are generated, and the query nodes are included in a graph. Leaf nodes for each of the aspects are generated. Connections between the leaf nodes and the query nodes are generated. A destination page that includes various aspects is generated.

Abstract: Example embodiments described herein disclose a specially configured device to generate and cause display of human readable titles for browse pages. The token based title system may be or include a group of one or more server machines. A user device may accordingly receive a search query and set of structured data elements (e.g., filter attributes), create a browse node based on the content of the search query and the structured data elements, access published content (e.g., an item inventory) based on the browse node, and generate a human readable page title to be displayed as a title of a browse page.

Abstract: 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.