TIME SERIES ALIGNMENT USING MULTISCALE MANIFOLD LEARNING

    公开(公告)号:US20220137930A1

    公开(公告)日:2022-05-05

    申请号:US17089838

    申请日:2020-11-05

    Applicant: ADOBE INC.

    Abstract: Systems and methods are described for performing dynamic time warping using diffusion wavelets. Embodiments of the inventive concept integrate dynamic time warping with multi-scale manifold learning methods. Certain embodiments also include warping on mixed manifolds (WAMM) and curve wrapping. The described techniques enable an improved data analytics application to align high dimensional ordered sequences such as time-series data. In one example, a first embedding of a first ordered sequence of data and a second embedding of a second ordered sequence of data may be computed based on generated diffusion wavelet basis vectors. Alignment data may then be generated for the first ordered sequence of data and the second ordered sequence of data by performing dynamic time warping.

    UTILIZING EMBEDDING-BASED CLAIM-RELATION GRAPHS FOR EFFICIENT SYNTOPICAL READING OF CONTENT COLLECTIONS

    公开(公告)号:US20240419921A1

    公开(公告)日:2024-12-19

    申请号:US18336380

    申请日:2023-06-16

    Applicant: Adobe Inc.

    Abstract: This disclosure describes one or more implementations of systems, non-transitory computer-readable media, and methods that extract viewpoints from content for syntopical reading using an efficient claim-relation graph construction approach. For example, the disclosed systems utilize sentence transformers with claims from content to embed the claims within a metric space (as claim nodes). Furthermore, in some embodiments, the disclosed systems generate a claim relation graph for the claims by utilizing approximate nearest neighbor searches to determine relational edges between a claim node and the claim node's approximate nearest neighbors. Moreover, in some implementations, the disclosed systems utilize the claim relation graph with an edge weighted graph neural network to determine stance labels during extraction of viewpoints (e.g., stance, aspect, and topic) for the claims. Additionally, in one or more instances, the disclosed systems utilize the extracted viewpoints in content retrieval applications (e.g., viewpoint ranked search results and/or socially contextualized claims).

    SPATIAL DOCUMENT SYSTEM AND METHOD

    公开(公告)号:US20240386675A1

    公开(公告)日:2024-11-21

    申请号:US18317851

    申请日:2023-05-15

    Applicant: Adobe Inc.

    Abstract: A computing system captures image data using a camera and captures spatial information using one or more sensors. The computing system receives voice data using a microphone. The computing system analyzes the voice data to identify a keyword. The computing system analyzes the image data and the spatial information to identify an object corresponding to the keyword. The computing system generates text based on the voice data and the keyword. The computing system stores the text in association with the object. The computing system generates and provides output comprising the text linked to the object or a derivative thereof.

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