公开(公告)号：US20250133427A1

公开(公告)日：2025-04-24

申请号：US18489800

申请日：2023-10-18

Applicant: DISH Wireless L.L.C.

Inventor： Tomer Danon ,  Ahmed Alkarboly ,  Jennings Orcutt ,  David Ricardo Bentolila Sapiani

IPC: H04W24/08 ,  H04L41/16

Abstract: Technologies for network drive test prioritization based on machine learning are disclosed. An example method includes feeding a representation of routes of a target candidate drive test to a trained machine learning model to obtain a drive test prediction, wherein the trained machine learning model is trained based on integrating radio frequency (RF) estimations or predictions with past drive test data. The method also includes sorting a set of candidate drive tests for the communications network including the target candidate drive test, based on drive test predictions associated with each candidate drive test, to determine priorities for executing drive tests; and determining expectation of network usability in accordance with network availability and performance metrics.

公开(公告)号：US20240296145A1

公开(公告)日：2024-09-05

申请号：US18117169

申请日：2023-03-03

Applicant: DISH Wireless L.L.C.

Inventor： Darshit Gandhi ,  Tomer Danon ,  Hamza Nasir Khokhar

IPC: G06F16/14 ,  G06F16/901

CPC classification number: G06F16/156 ,  G06F16/9024

Abstract: This disclosure relates to representing and using metadata via graph database. In some aspects, a method includes receiving, at one or more computing devices, first metadata associated with data files from one or more data sources, the first metadata representing a plurality of features of associated data included in the data files, the plurality of features including at least one of a file name, a table name, an attribute, a row name, and a column name; determining relationships among the plurality of features to generate second metadata representing content of the data files; and generating a graph database representing the content of the data files, the graph database including a set of nodes and a set of edges, wherein each node in the set of nodes represents a feature of the plurality of features, and each edge represents a relationship between two nodes in the set of nodes.