Patents by Inventor Su-Ming Wu

Su-Ming Wu has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20230297948
    Abstract: Embodiments predict supply chain policies using machine learning. A machine learning model trained to predict one or more supply chain metrics for a first product can be stored. The machine learning model can generate a plurality of supply chain metric predictions for the first product using a plurality of candidate replenishment policies for the first product. A candidate replenishment policy with a corresponding supply chain metric prediction that meets a criteria can be selected. The selected replenishment policy can be implemented for the first product within an inventory system, where one or more physical locations are restocked with the first product based on restocking parameters defined by the selected replenishment policy.
    Type: Application
    Filed: March 18, 2022
    Publication date: September 21, 2023
    Inventors: Setareh BORJIAN, Su-Ming WU, Shenghao WANG
  • Patent number: 11727348
    Abstract: Systems, methods, and other embodiments associated with self-tuning optimization of a replenishment policy of an item are described. In one embodiment, the method includes determining an initial replenishment policy of the item. A performance of the initial replenishment policy is determined based upon past performance of the initial replenishment policy. The initial replenishment policy is revised to get a service level of the item for future sales periods closer to a target service level of the item. Information is forwarded in real-time about the revised replenishment policy to an order fulfillment facility.
    Type: Grant
    Filed: November 19, 2020
    Date of Patent: August 15, 2023
    Assignee: Oracle International Corporation
    Inventors: Setareh Borjian Boroujeni, Su-Ming Wu
  • Patent number: 11663624
    Abstract: Systems, methods, and other embodiments associated with computing and generating schedule data structures for items in a display are described. In one embodiment, a method includes accessing a sales data structure corresponding to a store and analyzing sales records for items associated with subcategories to calculate a subcategory profit contribution score for each subcategory. The method may also include selecting a first subcategory from the subcategories as a candidate subcategory of items and analyzing the sales records to calculate an item profit contribution score for each of the items assigned to the candidate subcategory. A first item is selected from the candidate subcategory to be placed on a promotional display space, based upon the item profit contribution score of the first item. A schedule data structure is generated that assigns the first item to the promotional display space.
    Type: Grant
    Filed: December 14, 2021
    Date of Patent: May 30, 2023
    Assignee: Oracle International Corporation
    Inventors: Su-Ming Wu, Mark E. Ferguson, Olga Pak, Olga Perdikaki
  • Patent number: 11580339
    Abstract: Embodiments detect fraud of risk targets that include both customer accounts and cashiers. Embodiments receive historical point of sale (“POS”) data and divide the POS data into store groupings. Embodiments create a first aggregation of the POS data corresponding to the customer accounts and a second aggregation of the POS data corresponding to the cashiers. Embodiments calculate first features corresponding to the customer accounts and second features corresponding to the cashiers. Embodiments filter the risk targets based on rules and separate the filtered risk targets into a plurality of data ranges. For each combination of store groupings and data ranges, embodiments train an unsupervised machine learning model. Embodiments then apply the unsupervised machine learning models after the training to generate first anomaly scores for each of the customer accounts and cashiers.
    Type: Grant
    Filed: November 13, 2019
    Date of Patent: February 14, 2023
    Assignee: ORACLE INTERNATIONAL CORPORATION
    Inventors: William M. Warrick, II, Su-Ming Wu, Stephen Clegg, Randall Fernandes
  • Publication number: 20220284386
    Abstract: One example of computerized inventory redistribution control includes, for each location inventory record in a set of location inventory records, calculating a quantity change that will bring a current item quantity to a different item quantity for the location inventory record. Determining a cost of a minimum-cost redistribution among the physical locations to effect the quantity changes. Determining a scaling factor that maximizes total revenue when the quantity changes are scaled by the scaling factor after deducting the cost scaled by the scaling factor. Generating transfer instructions for a redistribution of the item by scaling the transfer quantities of the minimum-cost redistribution by the scaling factor. Transmitting each transfer instruction to a computing device associated with a physical location indicated in the transfer instruction.
    Type: Application
    Filed: May 26, 2022
    Publication date: September 8, 2022
    Inventors: Su-Ming WU, Kiran PANCHAMGAM, Bernard GRIFFITHS
  • Patent number: 11423344
    Abstract: Systems, methods, and other embodiments associated with generating a price schedule are described. In one embodiment, for each customer segment of a plurality of customer segments, a per-segment value of an approximate objective function for the customer segment is determined by an optimizer, and a ratio of the per-segment value to a sum of all per-segment values for the customer segments is computed. The inventory quantity is allocated amongst the customer segments according to the ratio for each customer segment to form an inventory quantity for each customer segment. For each customer segment, a promotion portion of the price schedule that maximizes the objective function by the optimizer is determined. A quantity of remaining inventory allocated to the plurality of customer segments at an end of the regular season is aggregated. A markdown portion of the price schedule for the item that maximizes the objective function is determined by the optimizer.
    Type: Grant
    Filed: December 23, 2019
    Date of Patent: August 23, 2022
    Assignee: Oracle International Corporation
    Inventors: Aswin Kannan, Kiran Panchamgam, Su-Ming Wu
  • Patent number: 11410117
    Abstract: Systems, methods, and other embodiments associated with controlling inventory depletion by offering different prices to different customers are described. In one embodiment, a method includes establishing first and second allocations of fulfillment centers to different geographic regions during a markdown phase. Different price schedules are determined for the orders to be fulfilled during the markdown phase based on the first and second allocations. A predicted profit is generated for the orders fulfilled under each of the different price schedules. A price schedule corresponding to the first allocation is selected as resulting in a greater predicted profit than another one of the different price schedules. A sale terminal is controlled to enact the selected price schedule during the markdown phase to cause fulfillment of the incoming orders according to the first allocation of the fulfillment centers.
    Type: Grant
    Filed: October 23, 2018
    Date of Patent: August 9, 2022
    Assignee: Oracle International Corporation
    Inventors: Su-Ming Wu, Andrew Vakhutinsky
  • Patent number: 11367042
    Abstract: One example of computerized inventory redistribution control includes, for each location inventory record in a set of location inventory records, calculating a quantity change that will bring a current item quantity to a different item quantity for the location inventory record. Determining a cost of a minimum-cost redistribution among the physical locations to effect the quantity changes. Determining a scaling factor that maximizes total revenue when the quantity changes are scaled by the scaling factor after deducting the cost scaled by the scaling factor. Generating transfer instructions for a redistribution of the item by scaling the transfer quantities of the minimum-cost redistribution by the scaling factor. Transmitting each transfer instruction to a computing device associated with a physical location indicated in the transfer instruction.
    Type: Grant
    Filed: April 5, 2019
    Date of Patent: June 21, 2022
    Assignee: Oracle International Corporation
    Inventors: Su-Ming Wu, Kiran Panchamgam, Bernard Griffiths
  • Patent number: 11321722
    Abstract: Systems, methods, and other embodiments associated with incrementally swapping items in an assortment are described. In one embodiment, a computing system includes demand logic configured to read data from an electronic data structure that defines an assortment. The assortment defines a subset of items from a product category. The demand logic is configured to generate forecasted changes to an associated metric value by generating demand transference values for (i) individually removing each item presently in the assortment and (ii) individually adding each item of a set of available items of the product category. The computing system includes assortment logic configured to transform the electronic data structure that defines the assortment according to the forecasted changes by incrementally swapping items in the assortment for new items in the available set of items until the forecasted changes between items in the assortment and new items in the set of available items satisfy a predefined condition.
    Type: Grant
    Filed: January 20, 2015
    Date of Patent: May 3, 2022
    Assignee: Oracle International Corporation
    Inventors: Su-Ming Wu, Saraswati Yagnavajhala
  • Publication number: 20220101373
    Abstract: Systems, methods, and other embodiments associated with computing and generating schedule data structures for items in a display are described. In one embodiment, a method includes accessing a sales data structure corresponding to a store and analyzing sales records for items associated with subcategories to calculate a subcategory profit contribution score for each subcategory. The method may also include selecting a first subcategory from the subcategories as a candidate subcategory of items and analyzing the sales records to calculate an item profit contribution score for each of the items assigned to the candidate subcategory. A first item is selected from the candidate subcategory to be placed on a promotional display space, based upon the item profit contribution score of the first item. A schedule data structure is generated that assigns the first item to the promotional display space.
    Type: Application
    Filed: December 14, 2021
    Publication date: March 31, 2022
    Inventors: Su-Ming WU, Mark E. FERGUSON, Olga PAK, Olga PERDIKAKI
  • Patent number: 11270326
    Abstract: Embodiments determine a price schedule for an item by, for each item, receiving a set of prices for the item, an inventory quantity for the item, a per-segment demand model for the item, and an objective function that is a function of the per-segment demand model and maximizes revenue based at least on a probability of a return of the item and a cost of the return. Embodiments allocate the inventory quantity among a plurality of customer segments based at least on a predicted contribution of each customer segment to the objective function. Embodiments determine a markdown portion of the price schedule for the item that maximizes the objective function, where the markdown portion assigns a series of prices selected from the set of prices for respective time periods during a clearance season for the item.
    Type: Grant
    Filed: April 10, 2019
    Date of Patent: March 8, 2022
    Assignee: ORACLE INTERNATIONAL CORPORATION
    Inventors: Su-Ming Wu, Andrew Vakhutinsky, Setareh Borjian Boroujeni, Santosh Bai Reddy, Kiran V. Panchamgam, Sajith Vijayan, Mengzhenyu Zhang
  • Publication number: 20220036289
    Abstract: Systems, methods, and other embodiments associated with self-tuning optimization of a replenishment policy of an item are described. In one embodiment, the method includes determining an initial replenishment policy of the item. A performance of the initial replenishment policy is determined based upon past performance of the initial replenishment policy. The initial replenishment policy is revised to get a service level of the item for future sales periods closer to a target service level of the item. Information is forwarded in real-time about the revised replenishment policy to an order fulfillment facility.
    Type: Application
    Filed: November 19, 2020
    Publication date: February 3, 2022
    Inventors: Setareh BORJIAN BOROUJENI, Su-Ming WU
  • Patent number: 11222357
    Abstract: Systems, methods, and other embodiments associated with computing and generating schedule data structures for items in a display are described. In one embodiment, a method includes accessing a sales data structure corresponding to a store and analyzing sales records for items associated with subcategories to calculate a subcategory profit contribution score for each subcategory. The method may also include selecting a first subcategory from the subcategories as a candidate subcategory of items and analyzing the sales records to calculate an item profit contribution score for each of the items assigned to the candidate subcategory. A first item is selected from the candidate subcategory to be placed on a promotional display space, based upon the item profit contribution score of the first item. A schedule data structure is generated that assigns the first item to the promotional display space.
    Type: Grant
    Filed: May 1, 2017
    Date of Patent: January 11, 2022
    Assignee: Oracle International Corporation
    Inventors: Su-Ming Wu, Mark E. Ferguson, Olga Pak, Olga Perdikaki
  • Patent number: 11151631
    Abstract: Embodiments provide a recommendation for an additional item in response to receiving a basket of goods determine a type for the basket of goods from a set of basket types, receive a set of additional targeted items as target recommendations and receive a history of received types of baskets of goods. Embodiments iteratively perform a clustering into a plurality of clusters of each of the basket types based on the history of received types of baskets of goods, and preference updating for each of the targeted items into each of the plurality of clusters. The iteratively performing, after a plurality of iterations, outputs a sequence of mappings and a sequence of preference parameters. Embodiments generate a frequency of tabulation of mappings from the sequence of mappings and then generate the recommendation based on the sequence of mappings, the sequence of preference parameters and the frequency of tabulation of mappings.
    Type: Grant
    Filed: April 17, 2018
    Date of Patent: October 19, 2021
    Assignee: ORACLE INTERNATIONAL CORPORATION
    Inventors: Sajad Modaresi, Fernando Bernstein, Denis Saure, Setareh Borjian Boroujeni, Su-Ming Wu, Robert Corr, Nikos Nikolakis
  • Publication number: 20210142126
    Abstract: Embodiments detect fraud of risk targets that include both customer accounts and cashiers. Embodiments receive historical point of sale (“POS”) data and divide the POS data into store groupings. Embodiments create a first aggregation of the POS data corresponding to the customer accounts and a second aggregation of the POS data corresponding to the cashiers. Embodiments calculate first features corresponding to the customer accounts and second features corresponding to the cashiers. Embodiments filter the risk targets based on rules and separate the filtered risk targets into a plurality of data ranges. For each combination of store groupings and data ranges, embodiments train an unsupervised machine learning model. Embodiments then apply the unsupervised machine learning models after the training to generate first anomaly scores for each of the customer accounts and cashiers.
    Type: Application
    Filed: November 13, 2019
    Publication date: May 13, 2021
    Inventors: William M. WARRICK, II, Su-Ming WU, Stephen CLEGG, Randall FERNANDES
  • Publication number: 20200380452
    Abstract: Embodiments optimize the inventory allocation of a retail item that is provided from a plurality of warehouses to a plurality of price zones, each of the warehouses adapted to allocate inventory of the retail item to at least two of the price zones via links. Embodiments generate an initial inventory allocation for each warehouse to price zone link to generate a plurality of warehouse to price zone allocations. For each of the warehouse to price zone allocations, embodiments determine a marginal profit as a function of inventory allocated. Embodiments construct a bi-partite graph corresponding to each warehouse to price zone allocation, each bi-partite graph having a link weight equal to the marginal profit. Embodiments determine when there is a positive weight path between any two price zones and then reallocate the initial inventory allocation and repeat the functionality.
    Type: Application
    Filed: May 30, 2019
    Publication date: December 3, 2020
    Inventors: Andrew VAKHUTINSKY, Kiran V. PANCHAMGAM, Su-Ming WU
  • Publication number: 20200342475
    Abstract: Embodiments determine a price schedule for an item by, for each item, receiving a set of prices for the item, an inventory quantity for the item, a per-segment demand model for the item, and an objective function that is a function of the per-segment demand model and maximizes revenue based at least on a probability of a return of the item and a cost of the return. Embodiments allocate the inventory quantity among a plurality of customer segments based at least on a predicted contribution of each customer segment to the objective function. Embodiments determine a markdown portion of the price schedule for the item that maximizes the objective function, where the markdown portion assigns a series of prices selected from the set of prices for respective time periods during a clearance season for the item.
    Type: Application
    Filed: April 10, 2019
    Publication date: October 29, 2020
    Inventors: Su-Ming WU, Andrew VAKHUTINSKY, Setareh Borjian BOROUJENI, Santosh Bai REDDY, Kiran V. PANCHAMGAM, Sajith VIJAYAN, Mengzhenyu ZHANG
  • Publication number: 20200320467
    Abstract: One example of computerized inventory redistribution control includes, for each location inventory record in a set of location inventory records, calculating a quantity change that will bring a current item quantity to a different item quantity for the location inventory record. Determining a cost of a minimum-cost redistribution among the physical locations to effect the quantity changes. Determining a scaling factor that maximizes total revenue when the quantity changes are scaled by the scaling factor after deducting the cost scaled by the scaling factor. Generating transfer instructions for a redistribution of the item by scaling the transfer quantities of the minimum-cost redistribution by the scaling factor. Transmitting each transfer instruction to a computing device associated with a physical location indicated in the transfer instruction.
    Type: Application
    Filed: April 5, 2019
    Publication date: October 8, 2020
    Inventors: Su-Ming WU, Kiran PANCHAMGAM, Bernard GRIFFITHS
  • Publication number: 20200126016
    Abstract: Systems, methods, and other embodiments associated with generating a price schedule are described. In one embodiment, for each customer segment of a plurality of customer segments, a per-segment value of an approximate objective function for the customer segment is determined by an optimizer, and a ratio of the per-segment value to a sum of all per-segment values for the customer segments is computed. The inventory quantity is allocated amongst the customer segments according to the ratio for each customer segment to form an inventory quantity for each customer segment. For each customer segment, a promotion portion of the price schedule that maximizes the objective function by the optimizer is determined. A quantity of remaining inventory allocated to the plurality of customer segments at an end of the regular season is aggregated. A markdown portion of the price schedule for the item that maximizes the objective function is determined by the optimizer.
    Type: Application
    Filed: December 23, 2019
    Publication date: April 23, 2020
    Inventors: Aswin KANNAN, Kiran PANCHAMGAM, Su-Ming WU
  • Patent number: 10628403
    Abstract: Systems, methods, and other embodiments associated with extracting attributes from electronic data structures are described. In one embodiment, a method includes correlating tokens from description strings with defined attributes in an electronic inventory database by identifying which of the defined attributes match the tokens to link the tokens with columns of the database associated with the defined attributes. The method includes iteratively updating annotation strings for unidentified ones of the tokens by generating suggested matches for the unidentified tokens according to known correlations between identified tokens and the defined attributes using a conditional random fields model. The method also includes populating the database using the identified tokens from the description strings according to the annotation strings by automatically storing the tokens from the description strings into the columns as identified by the annotation strings.
    Type: Grant
    Filed: January 27, 2016
    Date of Patent: April 21, 2020
    Assignee: Oracle International Corporation
    Inventors: Su-Ming Wu, Setareh Borjian Boroujeni