PERSONALIZED VISUALIZATION RECOMMENDATION SYSTEM

    公开(公告)号:US20220147540A1

    公开(公告)日:2022-05-12

    申请号:US17091941

    申请日:2020-11-06

    Applicant: ADOBE INC.

    Abstract: Systems and methods for personalized visualization recommendation are described. Embodiments of the described systems and methods are configured to identify a first matrix representing user interactions with a plurality of data attributes corresponding to a plurality of datasets, a second matrix representing user interactions with a plurality of visualizations, and a third matrix representing a plurality of meta-features for each of the data attributes; compute low-dimensional embeddings representing user characteristics, the data attributes, visualization configurations, and the meta-features using joint factorization of the first matrix, the second matrix and the third matrix; generate a model for predicting visualization preference weights based on the low-dimensional embeddings; predict the visualization preference weights for a user corresponding to a plurality of candidate visualizations of dataset using the model; and generate a personalized visualization of the dataset for the user based on the predicted visualization preference weights.

    Dynamic clustering of sparse data utilizing hash partitions

    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.

    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.

    Network-based probabilistic device linking

    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.

    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.

    Associating user logs using geo-point density

    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.

    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.

    Analytics System Entity Resolution
    55.
    发明申请

    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.

    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.

    Organizing electronically stored files using an automatically generated storage hierarchy

    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.

    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.

    Higher-order network embedding
    57.
    发明授权

    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.

    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.

    Time-Dependent Network Embedding
    58.
    发明申请

    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.

    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.

    LANGUAGE MODELS FOR READING CHARTS
    60.
    发明公开

    公开(公告)号:US20240311403A1

    公开(公告)日:2024-09-19

    申请号:US18183997

    申请日:2023-03-15

    Applicant: ADOBE INC.

    CPC classification number: G06F16/3329 G06F16/3325

    Abstract: Systems and methods for natural language processing are described. Embodiments of the present disclosure obtain a chart and a query via a user interface. An answer model generates an answer to the query based on the chart, wherein the answer model comprises a machine learning model trained based on chart data for the chart. A description model generates a visual description based on the answer and the chart, wherein the description model comprises a machine learning model trained based on a chart specification for the chart. A response component transmits a response to the query based on the answer and the visual description.

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