18560756. CLASSIFYING DATA OBJECTS USING NEIGHBORHOOD REPRESENTATIONS (Google LLC)
CLASSIFYING DATA OBJECTS USING NEIGHBORHOOD REPRESENTATIONS
Organization Name
Inventor(s)
Oleg Golubitsky of Guelph (CA)
CLASSIFYING DATA OBJECTS USING NEIGHBORHOOD REPRESENTATIONS
This abstract first appeared for US patent application 18560756 titled 'CLASSIFYING DATA OBJECTS USING NEIGHBORHOOD REPRESENTATIONS
Original Abstract Submitted
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for classifying data objects. One of the methods includes maintaining a dataset including reference data objects that each have one or more labels, one or more features, or both; receiving a request to add, to the dataset, a new data object that has one or more features but is missing one or more labels; selecting N neighbor data objects based on similarity scores of the neighbor data objects with respect to the new data object; generating a neighborhood feature vector for the new data object; processing the neighborhood feature vector using a machine learning model to predict the one or more labels for the new data object; and updating the dataset to include the new data object and to associate the one or more predicted labels with the new data object.