公开(公告)号：US20200004836A1

公开(公告)日：2020-01-02

申请号：US16147444

申请日：2018-09-28

Applicant: Apple Inc.

Inventor： Vivek Kumar RANGARAJAN SRIDHAR ,  Xingwen XU ,  Vignesh JAGADEESH

IPC: G06F17/30

Abstract: A device implementing a system for expanded search includes a processor configured to identify plural words, and generate, for each word of the plural words, a word vector based on a proximity of the word relative to other words of the plural words, the word vector comprising plural dimensions. The processor is further configured to create a compressed word vector structure comprising clusters of subsets of the plural dimensions across the word vectors, each cluster including similar values of the respective dimensions, convert the word vectors to points on at least one plane, and partition the at least one plane into nested groupings of the points based on a threshold number of points per nested grouping. The processor is further configured to create a tree look-up structure of the nested groupings, and provide the compressed word vector structure and the tree look-up structure to a client device.

公开(公告)号：US20220093088A1

公开(公告)日：2022-03-24

申请号：US17031798

申请日：2020-09-24

Applicant: Apple Inc.

Inventor： Vivek Kumar RANGARAJAN SRIDHAR ,  Barada Prasanna Acharya ,  Douglas Ross Davidson ,  Xingwen XU

IPC: G10L15/197 ,  G10L15/18

Abstract: Methods and systems for embedding natural language sentences within a highly-dimensional vector space are provided. Additionally, various applications relating to natural language processing, are provided. Such applications include digital assistants and search engines, as well as systems for classifying, sorting, organizing, and/or pairing content that are associated with natural language objects. The sentence vector embeddings encode various semantic features of the sentence. Two separate language models, arranged in a serial architecture are employed to generate a sentence vector. The first language model generates token vectors for each of the tokens included in the sentence. The token vectors are employed as inputs to the second language model. The second language model generates the sentence vector for the sentence. A sentence vector embeds the semantic context of the corresponding natural language object within the vector space. The second language model may be trained via supervised learning on multiple semantic-related tasks.

公开(公告)号：US20180349447A1

公开(公告)日：2018-12-06

申请号：US15694267

申请日：2017-09-01

Applicant: Apple Inc.

Inventor： William C. MACCARTNEY ,  Ahmed S. ELDEEB ,  Paul J. PELZL ,  Vivek Kumar RANGARAJAN SRIDHAR ,  Xingwen XU

IPC: G06F17/30

CPC classification number: G06F17/30867

Abstract: Systems and processes for operating an intelligent automated assistant to provide customized suggestions based on user-specific information. An example method includes, at an electronic device having one or more processors, obtaining impressions associated with at least one of the electronic device or additional electronic devices communicatively coupled to the electronic device; and determining one or more concepts based on the impressions. The method also includes generating, based on the one or more determined concepts, a representation of a collection of user-specific information; and providing one or more suggestions to a user based on the representation of the collection of user-specific information.