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案件記録

ADD-IN RECOMMENDATION SYSTEM

発明審査中
2閲覧数
20請求項 · 3 独立
§ Ⅰ

案件概要

発明者

Sayan CHALIHA; Meghna MANJAREE; Rama Kant PATHAK; Padmanabhan SUNDARARAJAN; Rajiv SRIVASTAVA; Nikita MITTAL; Poonam SAVALE; Snigdha VERMA; Arul Prabhu R; Teekam Chand GOYAL

IPC分類

G6F 16/958G6F 16/955

CPC分類

G6F16/958G6F16/9558

An add-in recommendation system receives add-in recommendation requests from an add-in recommendation client which includes context information pertaining to user interactions with a client application. The context information is mapped to an embedding space using an encoder to generate a context embedding. An add-in recommendation engine compares the context embedding to an add-in index using to identify a predetermined number of add-in deep links to include in an add-in recommendation. The add-in index includes a plurality of add-in embeddings, each add-in embedding being associated with an add-in deep link which is accessible to the user and being used to map a semantic description of the add-in deep link to the embedding space. The add-in recommendation to the add-in recommendation client and displayed in a user interface of the client application.

原文(中国語)

An add-in recommendation system receives add-in recommendation requests from an add-in recommendation client which includes context information pertaining to user interactions with a client application. The context information is mapped to an embedding space using an encoder to generate a context embedding. An add-in recommendation engine compares the context embedding to an add-in index using to identify a predetermined number of add-in deep links to include in an add-in recommendation. The add-in index includes a plurality of add-in embeddings, each add-in embedding being associated with an add-in deep link which is accessible to the user and being used to map a semantic description of the add-in deep link to the embedding space. The add-in recommendation to the add-in recommendation client and displayed in a user interface of the client application.

外部リソース