Anaplan. has been granted a patent for a method that processes categorical data in time series. The method involves generating categorical and supporting components, combining them to assess linear effects, predicting future categorical data, and displaying the forecast to users. GlobalData’s report on Anaplan 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 Anaplan, M2M communication interfaces was a key innovation area identified from patents. Anaplan's grant share as of June 2024 was 70%. Grant share is based on the ratio of number of grants to total number of patents.
Method for forecasting categorical data in time series
The patent US11995093B1 outlines a method for processing categorical data within a time series framework. This method involves obtaining a time series that consists of multiple entries and generating a categorical data component for each entry, which is 1-hot encoded. The process includes creating a supporting component and combining it with the categorical data component to specify the linear effect of the categorical data on the time series entries. A linear regression model is applied to predict historical values and extract weights for each entry, which are then combined with the 1-hot encoded values to form a combined categorical data component. This component is utilized to forecast future categorical data, which is subsequently displayed to the user.
The claims further detail specific applications of the method, such as the categorical data component representing holidays or events like sales discounts and promotions. Additionally, the method allows for the generation of multiple categorical data components for each entry, enabling the handling of cases where an entry is associated with multiple non-zero categorical components. The patent also describes the use of time series supportive data and sparse categorical data, with provisions for fitting the linear regression model using this data. The system is designed to be executed on a computer processor, facilitating the processing and forecasting of categorical data in a structured manner.
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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.
