Walmart. has been granted a patent for a system that generates target labels for sellers using multi-dimensional time series data. The system analyzes seller parameters, calculates aggregated metrics, clusters sellers into personas, and assigns labels such as “bad seller” or “high volume seller” to enhance classification on retail platforms. GlobalData’s report on Walmart gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Walmart, Transaction splitting was a key innovation area identified from patents. Walmart's grant share as of July 2024 was 38%. Grant share is based on the ratio of number of grants to total number of patents.
Generating target labels for seller classification using data
The patent US12073423B2 describes a sophisticated system designed to analyze and classify sellers on a retail platform using a combination of input parameters, scalar and vectorial data, and advanced processing techniques. The system comprises a computing device equipped with a processor, input, processing, and output systems. It receives parameters related to multiple sellers, generates time series metrics, and collects relevant data such as geolocation and payment information. The processing system performs feature selection and clustering using a Gaussian Mixture Model to create seller persona clusters based on aggregated metrics and seller characteristics. An overall score is calculated to assess the separation of these clusters, and if the score meets a predetermined threshold, the clusters are transmitted to the output system.
The output system generates target labels for each seller persona cluster, categorizing sellers as bad, high volume, seasonal, high customer dispute, or fraudulent. This labeled data is then used to train a supervised machine learning model, which can classify and detect sellers on the platform. The method also includes provisions for refining clusters if the overall score falls below the threshold and for identifying patterns within clusters to apply labels to future sellers exhibiting similar characteristics. The system is designed to enhance the accuracy and efficiency of seller classification, ultimately improving the retail platform's operational integrity.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
