Patents by Inventor Setareh BORJIAN BOROUJENI

Setareh BORJIAN BOROUJENI 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).

  • 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: 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: 20210117873
    Abstract: Embodiments provide optimized room assignments for a hotel in response to receiving a plurality of hard constraints and soft constraints and receiving reservation preferences and room features. The optimization includes determining a guest satisfaction assignment cost based on the reservation preferences and room features, determining an operational efficiency assignment cost, generating a weighted cost matrix based on the guest satisfaction assignment cost and the operational efficiency assignment cost, and generating preliminary room assignments based on the weighted cost matrix. When the preliminary room assignments are feasible, the preliminary room assignments are the optimized room assignments comprising a feasible selection of elements of the matrix. When the preliminary room assignments are infeasible, embodiments relax one or more constraints and repeat the performing optimization until the preliminary room assignments are feasible.
    Type: Application
    Filed: January 7, 2020
    Publication date: April 22, 2021
    Inventors: Andrew VAKHUTINSKY, Setareh Borjian BOROUJENI, Saraswati YAGNAVAJHALA, Jorge Luis Rivero PEREZ, Dhruv AGARWAL, Akash CHATTERJEE
  • 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
  • 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
  • Publication number: 20190318410
    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: Application
    Filed: April 17, 2018
    Publication date: October 17, 2019
    Inventors: Sajad MODARESI, Fernando BERNSTEIN, Denis SAURE, Setareh Borjian BOROUJENI, Su-Ming WU, Robert CORR, Nikos NIKOLAKIS
  • Publication number: 20190066128
    Abstract: Systems, methods, and other embodiments associated with predicting customer behavior are described. The method can include identifying a group comprising customers who satisfy a defined criterion, and receiving input that identifies a factor that influences a decision by the customers to purchase a product. A likelihood that the factor will induce the customers in the group to purchase the product is generated. A customer influence on the generated likelihood is estimated independently of data expressly identifying relationships between the customers in the group. The likelihood is modified by combining the likelihood and the customer influence according to a predictive model, and one or more of the customers eligible for a promotional offer related to the product is identified based, at least in part, on the modified likelihood. Transmission of the promotional offer is controlled to transmit the promotional offer to the identified customers in the group.
    Type: Application
    Filed: August 24, 2017
    Publication date: February 28, 2019
    Inventors: Lennart BAARDMAN, Tamar COHEN, Setareh BORJIAN BOROUJENI, Kiran PANCHAMGAM, Georgia PERAKIS
  • Publication number: 20170212921
    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: Application
    Filed: January 27, 2016
    Publication date: July 27, 2017
    Inventors: Su-Ming WU, Setareh BORJIAN BOROUJENI