Walmart Apollo, LLC

Servicenow, Inc.

Wal-mart Stores, Inc.

Rupert Labs, Inc.

Madhusudan Mathihalli

Shankara Bhargava Subramanya

Guoxun Yuan

Mitul Tiwari

Ravi Narasimhan Raj

Deepak Bobbarjung

Girish Natarajan

Quaizar Vohra

Digvijay Singh Lamba

Kaushik Rangadurai

Srivatsava Daruru

Jagannath Putrevu

Arvind Batra

Abhisaar Yadav

Anand Rajaraman

Feng Guo

Taraka Subrahmanya Prasad Siripurapu

Nikesh Garera

Junhao Jiang

Chris Bolte

Jebakumar Mathuram Santhosm Swvigaradoss

Tao Zhu

Sakshi Kataria

Molugu Sainithin

Kurt MacDonald

Ron Tal

Indrani Chakravarty

Aman Jain

Nidhi Garg

An input document data is received. The input document data is analyzed to automatically identify one or more response fields and one or more corresponding text labels laid out in the input document data. A conversation bot is automatically configured to provide one or more requests to provide one or more responses corresponding to the one or more response fields, receive the one or more responses, and store the one or more responses in a persistent computer storage.

Automatic conversation bot generation using input form

Example data processing systems and methods are described. In one implementation, a system accesses a corpus of data and analyzes the data contained in the corpus of data to identify multiple documents. The system generates vector indexes for the multiple documents such that the vector indexes allow a computing system to quickly access the plurality of documents and identify an answer to a question associated with the corpus of data.

Generation and utilization of vector indexes for data processing systems and methods

Data processing systems and methods

Example systems and methods related to chatbot skills are described. In one implementation, a system initiates a session to create a new chatbot. The system receives a selection of a first chatbot skill associated with the new chatbot and a selection of a second chatbot skill associated with the new chatbot, where the first chatbot skill is different from the second chatbot skill. The system creates the new chatbot by importing the first chatbot skill and the second chatbot skill into the new chatbot.

Chatbot skills systems and methods

A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more computer processors and perform configuring one or more advertisements for a sponsored product customized to fit a page type associated with a page format of a website; analyzing one or more inputs to create merged data; generating a respective rank of the advertisements of the sponsored product using a conversion probability; adjusting the respective rank the one or more advertisements of the sponsored product as a function of the merged data; automatically designating one of the one or more advertisements of the sponsored product that is ranked higher than other advertisements to be positioned closest to a predefined portion of a webpage; and sending instructions to display the one of the one or more advertisements closest to the predefined portion of the webpage of the website. Other embodiments are disclosed.

System for page type based advertisement matching for sponsored product listings on e-commerce websites and method of using same

Systems and methods including one or more processing modules and one or more non-transitory storage modules storing computing instructions configured to run on the one or more processing modules and perform acts of collecting training attribute values for a set of attributes; generating a probability model using the training attribute values, the probability model providing predicted outcomes for at least one attribute in the set of attributes; identifying, using the probability model, a first predicted outcome corresponding to a subsequent combination of attribute values collected by a collection module, wherein the predicted outcomes can comprise the first predicted outcome; coordinating a first display of an ad content version of a subsequent webpage when the first predicted outcome satisfies an objective of the subsequent webpage, wherein the first display can comprise: (a) an ad at a first location on the subsequent webpage and a webpage content in a first format at a second location on the subsequent webpage; or (b) the ad at a third location on the subsequent webpage and the webpage content in a second format at a fourth location on the subsequent webpage; and coordinating a second display of an ad-free version of the subsequent webpage when the first predicted outcome does not satisfy the objective of the subsequent webpage. Other embodiments are disclosed herein.

Management of the display of online ad content consistent with one or more performance objectives for a webpage and/or website

A system and method includes configuring a computer system to provide output of one or more advertisements of products to a user device of a consumer, receiving, by the computer system, one or more inputs of impressions, clicks, orders and other KPIs, estimating, by the computer system, for a click through rate (CTR) of advertisements of the products based on the inputs received, optimizing, by the computer system with an optimization module, an estimated revenue and estimated advertisement spending (Adspend) based on the CTR of advertisements, and providing, by the computer system, output of one or more advertisements of the products to the user device of the consumer for display.

System for optimizing sponsored product listings for seller performance in an e-commerce marketplace and method of using same

Systems and methods including one or more processing modules and one or more non-transitory storage modules storing computing instructions configured to run on the one or more processing modules and perform acts of receiving, from a plurality of entities, objectives and budgets associated with a plurality of keywords, determining cost-per-click (CPC) bids for each of the entities for some of the plurality of keywords using the objectives and the budgets, determining internal bids by the plurality of entities for the plurality of keywords by multiplying the CPC bid and a pacing multiplier, performing one or more iterative internal auctions, determining a highest bidder for each keyword of the plurality of keywords, and coordinating bidding by only the highest bidding entity for each of the keywords on a third-party external auction.

Systems and methods for a search engine marketing internal auction system

A system and method includes receiving, by a computer system, one or more inputs of customer level information, advertisement page and page type level information, item level information, inventory constraints, competitor pricing, and seasonal requirements/rules, merging, by the computer system, the one or more inputs, receiving, by the computer system including a module selection and ranking engine, the merged data, and providing, by the computer system, output of one or more advertisements of sponsored product listings to a user device of a consumer for display.

Systems and methods are disclosed for managing the display of online ad content consistent with one or more e-commerce objectives. A collection module may be operable to collect attribute values for a set of attributes characterizing user visits to a set of training webpages and subsequent attribute values for a subsequent user visit to a subsequent webpage. A model-generation module may be operable to train a probability model with the attribute values that predicts outcomes for at least one performance metric. A display module may be operable to determine whether to display ad content on the subsequent webpage for the subsequent user visit depending on whether a predicted outcome from the probability model that is relevant to the subsequent attribute values is consistent with one or more e-commerce objectives. The probability model may be a decision tree with different predicted outcomes for different combinations of attribute values.

Systems and methods are provided for processing a data stream in real time to identify connections between one or more social elements social elements and aggregating and storing the identified connections over a rolling time window. Social elements may be stored as nodes and connection between social elements may be stored as labeled connections between nodes. Other embodiments are provided.

Social genome

A method of extending an existing product taxonomy for an inventory of products. The existing product taxonomy can include pages having a hierarchical tree structure. The method can include determining a first set of keywords. The first set of keywords can be a prediction of keywords searched above a predetermined threshold during a predetermined time period of one or more external search engines. The method also can include generating dynamic product groups based on the first set of keywords. The method further can include generating a relation graph of the dynamic product groups. The relation graph can include relation links between the dynamic product groups. The method also can include linking the dynamic product groups to pages in the existing product taxonomy to generate an extended product taxonomy. The extended product taxonomy can include the existing product taxonomy, the dynamic product groups, and the relation links of the relation graph between the dynamic product groups. The method further can include presenting to a user information about the dynamic product groups. Other embodiments are provided.

Dynamic taxonomy generation with demand-based product groups

Systems and methods are provided for processing a data stream in real time to identify connections between one or more social elements social elements and aggregating and storing the identified connections over a rolling time window. Social elements may be stored as nodes and connection between social elements may be stored as labeled connections between nodes.

Exemplary embodiments provide methods, systems and devices for recommending one or more products for a selected individual. The products may be recommended to a user for gifting to the selected individual. Exemplary embodiments may automatically determine one or more topics of interest to the selected individual. In an exemplary embodiment, semantic analysis may be performed on textual content associated with the selected individual to automatically extract the topics of interest. Exemplary embodiments may use the topics of interest to automatically determine one or more products that are likely to be of interest to the selected individual.

Growing community of inventors

Saratoga, CA, United States of America

Madhusudan Mathihalli