Mobility Platform
AssigneeSHAED, Inc.
InventorsRyan Pritchard, Eddie Schick
Life of this patent
Estimating the term…
Abstract
A vehicle recommendation system comprising: a specialized data normalization architecture comprising a semantic understanding to automatically map diverse data schemas to a unified vehicle representation model; a specialized transformer architecture associated with a graph-based data representation to capture complex multi-stakeholder relationships associated with vehicle transactions and track the temporal evolution of the complex multi-stakeholder relationships; and a multi-objective optimization sub-system comprising reinforcement learning architecture to balance vehicle transactions constraints in real-time by generating optimal transaction parameters.
Claims20
A vehicle recommendation system comprising:
- a specialized data normalization architecture comprising a semantic understanding to automatically map diverse data schemas to a unified vehicle representation model;
- a specialized transformer architecture associated with a graph-based data representation to capture complex multi-stakeholder relationships associated with vehicle transactions and track temporal evolution of the complex multi-stakeholder relationships;
- and
- a multi-objective optimization sub-system comprising reinforcement learning architecture to balance vehicle transactions constraints in real-time by generating optimal transaction parameters.
An integrated system for vehicle procurement comprising:
- a circuit for performing neural network computations for a neural network comprising a plurality of layers, wherein receive raw data from a plurality of data sources, wherein the raw data comprises a plurality of formats, the circuit comprising:
- a data normalization layer for transforming raw data in disparate formats acquired from a plurality of data sources into structured data in a standardized data format, and comprising data cleaning and preprocessing techniques to handle missing values and outliers;
- and for applying feature scaling for consistent ranges across the plurality of data sources;
- a feature extraction layer for identifying relevant attributes from the structured data to form training data;
- a prediction layer for vehicle pricing and valuation predictions using the training data to train predictive models;
- and
- a recommendation layer comprising collaborative filters to provide personalized vehicle inventory recommendations.
A computer-implemented method for procuring a custom vehicle, a computer comprising a hardware processor and a memory device on which instructions are encoded to cause the hardware processor to perform the steps of:
- receiving raw data from a plurality of data sources, wherein the raw data comprises a plurality of formats and preprocessing the raw data;
- extracting predefined content from the raw data to generate feature vectors;
- generating a training data set and a test data set from output of the feature vector;
- training at least one machine learning model using the training data set and test data set to generate recommendations for the custom vehicle based on at least one of user preferences, vehicle type, body type, components, grants, financing, vehicle support infrastructure, jurisdiction;
- and
- outputting a report comprising information of the custom vehicle for facilitating procurement of the vehicle.
Dependencies are inferred from the claim text.