SYSTEMS AND METHODS FOR IDENTIFYING A MEANING OF AN AMBIGUOUS TERM IN A NATURAL LANGUAGE QUERY

    公开(公告)号:US20240362282A1

    公开(公告)日:2024-10-31

    申请号:US18654543

    申请日:2024-05-03

    申请人: Rovi Guides, Inc.

    摘要: Methods and systems for identifying a meaning of an ambiguous term in a natural language query. The media guidance application isolates first and second terms from a query received from a user and identifies, in a knowledge graph, first and second pluralities of candidate components associated with the first and second terms. The first and second terms each having multiple candidate components indicates the first and second terms have ambiguous meanings. The media guidance application matches each candidate component of the first and second pluralities of candidate components to form a plurality of pairs and determines strength of association for each pair in the plurality of pairs. The media guidance application filters the plurality of pairs by strength of association for each pair and determines a plurality of possible meanings based on the filtered plurality of pairs. The media guidance application selects a meaning from the plurality of possible meanings.

    System and method for depth data coding

    公开(公告)号:US12113949B2

    公开(公告)日:2024-10-08

    申请号:US18088207

    申请日:2022-12-23

    申请人: Rovi Guides, Inc.

    摘要: Systems and methods for encoding/decoding a 3D image are provided. The system decomposes depth map into a plurality of component depth maps (CDMs) for a plurality of depth ranges, wherein each component depth map corresponds to a focal plane of a multiple focal plane (MFP) decomposition of the image data. The system generates a plurality of component depth map focal planes (CDMFPs) by combining each respective CDM with the depth map. The system scales data in each CDMFP by a respective scaling factor. The system generates for transmission a plurality of encoded scaled CDMFP data streams for the plurality of depth ranges, wherein each respective scaled CDMFP data stream is based at least in part on a respective scaled CDMFP.