Walmart Apollo, LLC

Rahul D Sharnagat

Min Xie

Sreenivasa Prasad Sista

Hrushikesh Mohapatra

Lili Yuan

Qianwen Xie

Shirong Xue

Behnoush Abdollahi

This application relates to apparatus and methods for providing recommended items based on a search request. In some examples, a computing device determines a plurality of items for recommendation based on an item type in the search request from a user. The computing device then determines a model variant from a plurality of variants for each item based on a requested variant in the search request. The computing device generates item recommendations by modifying an item title for each of the plurality of items to indicate the corresponding model variant. The computing device then presents the item recommendations for the user's perusal.

System, method, and non-transitory computer readable medium for generating recommendations

This application relates to systems and methods for automatically generating experiments based on experiment requests routed to micro-services (model sub-components) using a prefix-based routing mechanism. In some examples, experiment requests may parsed to determine lower layer services (e.g., components) whose properties need to be changed for a model iteration. Prefixes in requests may be used to route the experiment requests and portions thereof to appropriate services or layers for configuration at the micro-service level. Routing tables at each higher layer may be utilized to determine the correct sub-layers to redirect a request and/or portion thereof. At micro-service level, each micro-service may store and use a configuration table to match a received parameter in a request with a property and its corresponding value for the experiment.

Systems and methods for testing models

An approach is disclosed for mapping an intent of a query. The approach receives query data for one or more queries. The approach determines product type data of the one or more queries. The approach determines attribute data for the determined product type data. The attribute data includes sequence attribute data and sequence value data. The approach retrieves catalog data for one or more items that include product type data that matches the determined product type data. The catalog data includes catalog attribute data and catalog value data. The approach determines engagement data for the one or more received queries. The engagement data includes a number of times customers interacted with a retrieved item for a respective query. The approach determines cumulative engagement data based on the retrieved catalog data and the determined engagement data. The approach generates a probability and an evaluation score based on the cumulative engagement data.

Query intent mapping

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Sunnyvale, CA, United States of America

Rahul D Sharnagat