Automatic Data Processing. has filed a patent for a method of sparse intent clustering. The method involves encoding features from electronic user reports into binary vectors, feeding them into an autoencoder neural network, and clustering them based on cosine similarities to identify user intents. GlobalData’s report on Automatic Data Processing 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 Automatic Data Processing, Digital lending was a key innovation area identified from patents. Automatic Data Processing's grant share as of January 2024 was 59%. Grant share is based on the ratio of number of grants to total number of patents.
Sparse intent clustering method using autoencoder neural network
A recently filed patent (Publication Number: US20240037003A1) describes a system that includes processors coupled with memory to create electronic reports based on user instructions. The system determines the intent of the report based on the provided title and description, identifies a vector cluster with a matching intent from a database of vector clusters, and provides relevant features for inclusion in the report. The processors generate vector clusters from previously generated reports, use a neural network to create compressed float vectors, and encode features into binary vectors for vector generation.
Furthermore, the system clusters vectors based on cosine similarities, projects them into a multi-dimensional space, and allows users to select specific features for their reports. The system is designed to cater to user-generated reports, ensuring that the vectors and clusters are based on the user's input. The method and computer-readable medium associated with the patent also outline similar processes for creating electronic reports, determining intent, identifying vector clusters, and providing relevant features for display. The instructions stored in the non-transitory computer-readable medium guide the processors to execute these functions efficiently, emphasizing the system's ability to streamline the report creation process based on user input.
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