- Patent Title: Systems and methods for estimating typed graphlets in large data
-
Application No.: US17008339Application Date: 2020-08-31
-
Publication No.: US11343325B2Publication Date: 2022-05-24
- Inventor: Ryan Rossi , Tung Mai , Anup Rao
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Agency: FIG. 1 Patents
- Main IPC: G06F15/173
- IPC: G06F15/173 ; H04L67/141 ; G06F17/18 ; G06F16/901

Abstract:
A system and method for fast, accurate, and scalable typed graphlet estimation. The system and method utilizes typed edge sampling and typed path sampling to estimate typed graphlet counts in large graphs in a small fraction of the computing time of existing systems. The obtained unbiased estimates of typed graphlets are highly accurate, and have applications in the analysis, mining, and predictive modeling of massive real-world networks. During operation, the system obtains a dataset indicating nodes and edges of a graph. The system samples a portion of the graph and counts a number of graph features in the sampled portion of the graph. The system then computes an occurrence frequency of a typed graphlet pattern and a total number of typed graphlets associated with the typed graphlet pattern in the graph.
Public/Granted literature
- US20220070266A1 SYSTEMS AND METHODS FOR ESTIMATING TYPED GRAPHLETS IN LARGE DATA Public/Granted day:2022-03-03
Information query