公开(公告)号：US20240362727A1

公开(公告)日：2024-10-31

申请号：US18560146

申请日：2022-05-11

Applicant: BAYERISCHE MOTOREN WERKE AKTIENGESELLSCHAFT

Inventor： Rainer MEHLHORN ,  Thomas WEBER

IPC: G06Q50/06 ,  G06Q30/0202 ,  G06Q40/04

CPC classification number: G06Q50/06 ,  G06Q30/0202 ,  G06Q40/04

Abstract: Systems, methods, and apparatuses are provided for operating an energy market platform for an energy trade for at least one aggregator using an electronic computing device. A time period is specified for the energy trade is subdivided into a multiplicity of time units. A respective energy potential is determined for each of the time units according to at least one energy system. The respective energy potential is represented so as to be visible to the aggregator on the energy market platform. A time-unit-dependent trade energy request is compared with the corresponding energy potential using an input by the aggregator. A multiplicity of at least partially electrically operated motor vehicles is provided. Using the energy market platform, the respective energy is determined such that, at a specific time point, a respective at least partially electrically operated motor vehicle assumes a specific energy volume.

公开(公告)号：US20240347214A1

公开(公告)日：2024-10-17

申请号：US18620442

申请日：2024-03-28

Applicant: Premier Healthcare Solutions, Inc.

Inventor： Shelley Parks Scavo ,  Jill Christy Jenkins ,  Nichole Ann Walton Barnes ,  Jessica Lynne Daley ,  Paula Gurz ,  Patrick Michael Sudol ,  Sudha Narayanaswamy

IPC: G16H70/40 ,  G06Q30/0202

CPC classification number: G16H70/40 ,  G06Q30/0202

Abstract: Systems, methods, and apparatuses are described herein for determining a drug shortage in an electronic environment. The present invention is configured to identify at least one drug identifier; identify at least one route type for the at least one drug resource identifier; determine at least one feature type associated with the at least one drug identifier, wherein each feature type comprises at least one attribute; generate a shortage score for the drug identifier; apply a post-score change to the shortage score, wherein the post-score change is based on at least one supplemental feature; and generate a drug shortage score based on the post-score change applied to the shortage score.

公开(公告)号：US20240346548A1

公开(公告)日：2024-10-17

申请号：US18749896

申请日：2024-06-21

Applicant: Kinaxis Inc.

Inventor： Kanchana PADMANABHAN ,  Anneya GOLOB ,  Brian KENG

IPC: G06Q30/0242 ,  G06F40/40 ,  G06N5/04 ,  G06N20/00 ,  G06Q30/0201 ,  G06Q30/0202 ,  G06Q30/0241 ,  G06Q30/0251

CPC classification number: G06Q30/0244 ,  G06F40/40 ,  G06N5/04 ,  G06N20/00 ,  G06Q30/0201 ,  G06Q30/0202 ,  G06Q30/0264 ,  G06Q30/0276

Abstract: Systems and methods for constraint-based optimization, comprising: an AI demand forecasting engine, an optimization engine, a user-defined objective, and a user-defined set of constraints. Using historical sales data, the AI demand forecasting engine generates a plurality of entities, each entity defined by a placement of an item in a promotion platform; and forecasts the objective associated with each entity. The optimization engine generates a plurality of plans, each plan consisting of a unique subset of entities. Plans that violate at least one constraint are eliminated by the optimization engine, leaving a set of candidate solutions. An optimum plan is selected from the set of candidate solutions based on maximization of the objective.

公开(公告)号：US20240346533A1

公开(公告)日：2024-10-17

申请号：US18740485

申请日：2024-06-11

Applicant: Microsoft Technology Licensing, LLC

Inventor： Mayank SHRIVASTAVA ,  Sagar GOYAL ,  Sahil BHATNAGAR ,  Pin-Jung CHEN ,  Pushpraj SHUKLA ,  Arko P. MUKHERJEE

IPC: G06Q30/0202 ,  G06N3/04 ,  G06N3/084 ,  G06N20/00

CPC classification number: G06Q30/0202 ,  G06N3/04 ,  G06N3/084 ,  G06N20/00

Abstract: The disclosure herein describes a system for generating embeddings representing sequential human activity by self-supervised, deep learning models capable of being utilized by a variety of machine learning prediction models to create predictions and recommendations. An encoder-decoder is provided to create user-specific journeys, including sequenced events, based on human activity data from a plurality of tables, a customer data platform, or other sources. Events are represented by sequential feature vectors. A user-specific embedding representing user activities in relationship to activities of one or more other users is created for each user in a plurality of users. The embeddings are updated in real-time as new activity data is received. The embeddings can be fine-tuned using labeled data to customize the embeddings for a specific predictive model. The embeddings are utilized by predictive models to create product recommendations and predictions, such as customer churn, next steps in a customer journey, etc.

公开(公告)号：US20240346531A1

公开(公告)日：2024-10-17

申请号：US18642834

申请日：2024-04-23

Applicant: Prevedere Inc.

Inventor： Loren Roger Marti ,  Richard Wagner ,  Elena Shatilova

IPC: G06Q30/0202

CPC classification number: G06Q30/0202

Abstract: The present invention relates to systems and methods for model scoring and selection. Six or more metrics that are relevant to the model are initially selected, and weights are assigned to each metric. A first subset of the metrics are selected, including metrics for model fit and model error for primary regression. A second subset of metrics including at least two penalty functions are then selected for percentage of incidence. The scores from the primary regression and penalty calculations are aggregated into a final score. Multiple models can be scored and utilized to select a “best” model via an iterative culling of low scoring models and “breeding” of the high scoring models.

公开(公告)号：US20240346438A1

公开(公告)日：2024-10-17

申请号：US18603014

申请日：2024-03-12

Applicant: Tata Consultancy Services Limited

Inventor： SAI RAVIKANTH PARVATAM LAKSHMI ,  MOHAN KRISHNAN ,  SAMEER VASANT AMBALKAR

IPC: G06Q10/087 ,  G06Q30/0202

CPC classification number: G06Q10/087 ,  G06Q30/0202

Abstract: Retail stores have limited visibility of on shelf inventory. Conventional approaches for targeted replenishment are reactive in nature and are also infrastructure and labor heavy. Present disclosure provides systems and methods for identification and replenishment of targeted items on shelves of stores wherein input data pertaining to sales of items is pre-processed and stock keeping unit (SKU) wise optimal bucket size is determined for predicting sales events for individual SKU based on historical events. Top-up requests are generated for each SKU for the planning bucket sizes and further a pick-up list using smart batching of the top-up requests is created based on SKU priorities. The pick-up list and top-up requests are executed to ensure items are topped up at the right time. Further, rate of sales or forecast the rate of sales are continually monitored throughout the day to ensure items are identified for targeted replenishment in retail stores.

公开(公告)号：US20240338715A1

公开(公告)日：2024-10-10

申请号：US18297856

申请日：2023-04-10

Applicant: Capital One Services, LLC

Inventor： Matthew NOWAK ,  Alexander GURFINKEL ,  Anna HUSAIN ,  Kamari CLARK

IPC: G06Q30/0202 ,  G06Q10/1093 ,  H04W4/029

CPC classification number: G06Q30/0202 ,  G06Q10/1095 ,  H04W4/029

Abstract: In some implementations, a device may retrieve one or more of: exchange data, account data, record data, interaction data, or metaverse data. The device may obtain at least one of location data or wireless network data, where the location data indicates a location, of a user device, associated with a first entity, and where the wireless network data indicates a wireless network, to which the user device has connected, associated with a second entity. The device may determine a probability of the user acquiring an item in a future time interval based on at least one of the exchange data, the account data, the record data, the interaction data, or the metaverse data, and at least one of first information relating to the first entity or second information relating to the second entity. The device may transmit information based on the probability of the user acquiring the item.

公开(公告)号：US20240338714A1

公开(公告)日：2024-10-10

申请号：US18296568

申请日：2023-04-06

Applicant: Naphtali David Rishe ,  Malek Adjouadi

Inventor： Naphtali David Rishe ,  Malek Adjouadi

IPC: G06Q30/0202 ,  G06Q50/16

CPC classification number: G06Q30/0202 ,  G06Q50/163

Abstract: Systems and methods for evaluating historical trends in real estate prices are provided. Systems and methods provide an understanding of historical price trends and assist in a property evaluation or appraisal, as well as allowing for an analysis of comparables in estimating a reasonable offer for a property on the market. Given a timespan of interest, a locale, and a category of properties of interest, an objective historical trend in values can be computed by first evaluating the ratios between the realized prices of transactions and objective governmental assessment of the properties at some fixed point of time. Then, for each period the ratios of all transactions in that period can be averaged, followed by comparing said averages between different time periods.

公开(公告)号：US12112290B2

公开(公告)日：2024-10-08

申请号：US18178741

申请日：2023-03-06

Applicant: Markison Patent Portal, Inc.

Inventor： Timothy W. Markison

IPC: G06Q10/0637 ,  G06F16/904 ,  G06F18/241 ,  G06Q10/10 ,  G06Q30/0202 ,  G06Q50/18

CPC classification number: G06Q10/06375 ,  G06F16/904 ,  G06F18/241 ,  G06Q10/103 ,  G06Q30/0202 ,  G06Q50/184 ,  G06F2216/11

Abstract: A computer includes an improved architecture of a computing entity (CE) processing core section, a technology level (TL) co-processor section, a system database section, and a memory section, which stores a CE operating system and a TL operating system. The database section stores TL data operands regarding quantified technologies and the memory section further stores TL system applications, and TL user applications. The CE processing core section executes the TL operating system and the CE operating system. The TL co-processor section executes TL system application(s), in accordance with control of the TL operating system and the CE operating system, to produce TL data operands regarding quantified technologies from a large number of MSBTP documents. The TL co-processor section executes TL user application(s), in accordance with control of the TL operating system and the CE operating system, to produce a digital representation of a characteristic of the quantified technology for display.

公开(公告)号：US20240320695A1

公开(公告)日：2024-09-26

申请号：US18734071

申请日：2024-06-05

Applicant: Newmark & Company Real Estate, Inc.

Inventor： Robert Bach

IPC: G06Q30/0202 ,  G06Q30/0645 ,  G06Q50/16

CPC classification number: G06Q30/0202 ,  G06Q30/0645 ,  G06Q50/16

Abstract: A system that comprises retrieving a plurality of factors from a real estate database. Each of the plurality of factors affect a momentum of a real estate market. A statistical model is applied to determine a set of factors that provide a greatest influence on an industrial momentum index. The set of factors are inputted into a formula in order to generate the industrial momentum index. The industrial momentum index is used to predict future real estate activities.