公开(公告)号：US11328002B2

公开(公告)日：2022-05-10

申请号：US16852110

申请日：2020-04-17

Applicant: Adobe Inc.

Inventor： Fan Du ,  Yeuk-Yin Chan ,  Eunyee Koh ,  Ryan Rossi ,  Margarita Savova ,  Charles Menguy ,  Anup Rao

IPC: G06F16/00 ,  G06F16/28 ,  G06F16/22 ,  G06F16/14 ,  G06F16/84 ,  G06F16/2458 ,  G06F16/909

Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods for utilizing hash partitions to determine local densities and distances among users (or among other represented data points) for clustering sparse data into segments. For instance, the disclosed systems can generate hash signatures for users in a sparse dataset and can map users to hash partitions based on the hash signatures. The disclosed systems can further determine local densities and separation distances for particular users (or other represented data points) within the hash partitions. Upon determining local densities and separation distances for datapoints from the dataset, the disclosed systems can select a segment (or cluster of data points) grouped according to a hierarchy of a clustering algorithm, such as a density-peaks-clustering algorithm.

公开(公告)号：US11184449B2

公开(公告)日：2021-11-23

申请号：US15214303

申请日：2016-07-19

Applicant: Adobe Inc.

Inventor： Nedim Lipka ,  Eunyee Koh

IPC: H04L29/08 ,  H04L12/24 ,  H04L12/741

Abstract: Network-based probabilistic device linking techniques are described that link multiple devices associated with a common entity. In one example, log records are received from service providers including a device identifier and an IP address associated with a computing device that uses the service providers to access resources. The received log records are filtered and analyzed to identify connection frequencies between each device identifier and various IP addresses. Connection frequencies are scored and used to identify a subset of connections for computing linked devices belonging to a common entity, such as a single user, a household of users, users in a specific location, and so on. Linked devices are computed from the subset of selected connections and combined into linked device clusters. These linked device clusters can then be output so that market analysis can be performed on the linked device cluster rather than data pertaining to a single device.

公开(公告)号：US10963527B2

公开(公告)日：2021-03-30

申请号：US16254125

申请日：2019-01-22

Applicant: ADOBE INC.

Inventor： Sungchul Kim ,  Nedim Lipka ,  Eunyee Koh

IPC: G06F16/29 ,  G06F16/9535 ,  G06F16/335

Abstract: A method for clustering geolocations using geo-point density includes receiving a user log of geolocation data extracted from user interactions with at least one electronic device. A density is determined relative to other geo-points for each geo-point in a set of geo-points extracted from the user log. Lower density geo-points in the set are merged into higher density geo-points in the set to result in a merged set of geo-points, and clusters of geo-points are identified from the merged set. Merging the geo-points tends to preserve frequently occurring geo-points while reducing those that constitute noise, which improves the reliability of identifying the clusters. Core geo-points of the user log are selected from the clusters. The core geo-points of the user log can be compared to core geo-points of other use logs to identify associations between the user logs.

公开(公告)号：US20210081473A1

公开(公告)日：2021-03-18

申请号：US16569484

申请日：2019-09-12

Applicant: Adobe Inc.

Inventor： Ryan A. Rossi ,  Sungchul Kim ,  Eunyee Koh ,  Anup Bandigadi Rao ,  Russell R. Stringham

IPC: G06F16/9535 ,  G06F16/955

Abstract: Techniques and systems are described for analytics system entity resolution. Typed higher-order node combinations are determined within a dataset, and an amount of similarity between two arbitrary nodes within the dataset is determined based on the typed higher-order node combinations. The amount of similarity enables the digital analytics to accurately perform source resolution of portions of the dataset to a respective source, and may be utilized to control output of digital content to a client device.

公开(公告)号：US10803037B2

公开(公告)日：2020-10-13

申请号：US15049172

申请日：2016-02-22

Applicant: Adobe Inc.

Inventor： Nedim Lipka ,  Tim Gollub ,  Eunyee Koh

IPC: G06F16/22 ,  G06F16/13 ,  G06F16/23

Abstract: Methods and systems are described that automatically organize directory hierarchies and label individual directories systematically. Upon a number of files in a first directory exceeding a maximum number of files, a second directory is created. The files formerly disposed only in the first directory are organized into both of the first directory and the second directory so that the threshold number of files is not exceeded in either of the first or second directories. Organizing the files into the first and second directories uses vector representations of each of the files generated by the system so that, when organized, the first and second directories each include files with similar content. Labels are selected for each of the directories based on a comparison between a vector representation of the collective contents of each directory and vector representations of titles in a database.

公开(公告)号：US10728105B2

公开(公告)日：2020-07-28

申请号：US16204616

申请日：2018-11-29

Applicant: Adobe Inc.

Inventor： Ryan A. Rossi ,  Eunyee Koh ,  Sungchul Kim ,  Anup Bandigadi Rao

IPC: H04L12/24 ,  G06F16/901 ,  G06N20/00 ,  H04L29/06

Abstract: In implementations of higher-order network embedding, a computing device maintains interconnected data in the form of a graph that represents a network, the graph including nodes that each represent entities in the network and node associations that each represent edges between the nodes in the graph. The computing device includes a network embedding module that is implemented to determine a frequency of k-vertex motifs for each of the edges in the graph, and derive motif-based matrices from the frequency of each of the k-vertex motifs in the graph. The network embedding module is also implemented to determine a higher-order network embedding for each of the nodes in the graph from each of the motif-based matrices. The network embedding module can then concatenate the higher-order network embeddings into a matrix representation.

公开(公告)号：US20200162340A1

公开(公告)日：2020-05-21

申请号：US16192313

申请日：2018-11-15

Applicant: Adobe Inc.

Inventor： Ryan A. Rossi ,  Sungchul Kim ,  Eunyee Koh

IPC: H04L12/24 ,  H04L12/26

Abstract: In implementations of time-dependent network embedding, a computing device maintains time-dependent interconnected data in the form of a time-based graph that includes nodes and node associations that each represent an edge between two of the nodes in the time-based graph based at least in part on a temporal value that indicates when the two nodes were associated. The computing device includes a network embedding module that is implemented to traverse one or more of the nodes in the time-based graph along the node associations, where the traversal is performed with respect to the temporal value of each of the edges that associate the nodes. The network embedding module is also implemented to determine a time-dependent embedding for each of the nodes traversed in the time-based graph, the time-dependent embedding for each of the respective nodes being representative of feature values that describe the respective node.

公开(公告)号：US20250036936A1

公开(公告)日：2025-01-30

申请号：US18358502

申请日：2023-07-25

Applicant: ADOBE INC.

Inventor： Ryan A. Rossi ,  Ryan Aponte ,  Shunan Guo ,  Jane Elizabeth Hoffswell ,  Nedim Lipka ,  Chang Xiao ,  Yeuk-yin Chan ,  Eunyee Koh

IPC: G06N3/08

Abstract: A method, apparatus, and non-transitory computer readable medium for hypergraph processing are described. Embodiments of the present disclosure obtain, by a hypergraph component, a hypergraph that includes a plurality of nodes and a hyperedge, wherein the hyperedge connects the plurality of nodes; perform, by a hypergraph neural network, a node hypergraph convolution based on the hypergraph to obtain an updated node embedding for a node of the plurality of nodes; and generate, by the hypergraph component, an augmented hypergraph based on the updated node embedding.

公开(公告)号：US12182493B2

公开(公告)日：2024-12-31

申请号：US18484674

申请日：2023-10-11

Applicant: Adobe Inc.

Inventor： Md Main Uddin Rony ,  Fan Du ,  Iftikhar Ahamath Burhanuddin ,  Ryan Rossi ,  Niyati Himanshu Chhaya ,  Eunyee Koh

IPC: G06F17/00 ,  G06F40/106 ,  G06F40/40

Abstract: Methods, computer systems, computer-storage media, and graphical user interfaces are provided for facilitating generation and presentation of insights. In one implementation, a set of data is used to generate a data visualization. A candidate insight associated with the data visualization is generated, the candidate insight being generated in text form based on a text template and comprising a descriptive insight, a predictive insight, an investigative, or a prescriptive insight. A set of natural language insights is generated, via a machine learning model. The natural language insights represent the candidate insight in a text style that is different from the text template. A natural language insight having the text style corresponding with a desired text style is selected for presenting the candidate insight and, thereafter, the selected natural language insight and data visualization are providing for display via a graphical user interface.

公开(公告)号：US20240311623A1

公开(公告)日：2024-09-19

申请号：US18183387

申请日：2023-03-14

Applicant: Adobe Inc.

Inventor： Ryan Rossi ,  Eunyee Koh ,  Jane Hoffswell ,  Nedim Lipka ,  Shunan Guo ,  Sudhanshu Chanpuriya ,  Sungchul Kim ,  Tong Yu

IPC: G06N3/049

CPC classification number: G06N3/049

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for building time-decayed line graphs from temporal graph networks for efficiently and accurately generating time-aware recommendations. For example, the time-decayed line graph system creates a line graph of the temporal graph network by deriving interaction nodes from temporal edges (e.g., timed interactions) and connecting interactions that share an endpoint node. Then, the time-decayed line graph system determines the edge weights in the line graph based on differences in time between interactions, with interactions that occur closer together in time being connected with higher weights. Notably, by using this method, the derived time-decayed line graph directly represents topological proximity and temporal proximity. Upon generating the time-decayed line graphs, the system performs downstream predictive modeling such as predicted edge classifications and/or temporal link predictions.