公开(公告)号：US20210157845A1

公开(公告)日：2021-05-27

申请号：US16697948

申请日：2019-11-27

Applicant: Amazon Technologies, Inc.

Inventor： Jean-Pierre DODEL ,  Zhiheng HUANG ,  Xiaofei MA ,  Ramesh M. NALLAPATI ,  Krishnakumar RAJAGOPALAN ,  Milan SAINI ,  Sudipta SENGUPTA ,  Saurabh Kumar SINGH ,  Dimitrios SOULIOS ,  Ankit SULTANIA ,  Dong WANG ,  Zhiguo WANG ,  Bing XIANG ,  Peng XU ,  Yong YUAN

IPC: G06F16/901 ,  G06F16/903 ,  G06F16/2457 ,  G06N3/04

Abstract: Techniques for searching documents are described. An exemplary method includes receiving a document search query; querying at least one index based upon the document search query to identify matching data; fetching the identified matched data; determining one or more of a top ranked passage and top ranked documents from the set of documents based upon one or more invocations of one or more machine learning models based at least on the fetched identified matched data and the document search query; and returning one or more of the top ranked passage and the proper subset of documents.

公开(公告)号：US20210157857A1

公开(公告)日：2021-05-27

申请号：US16698080

申请日：2019-11-27

Applicant: Amazon Technologies, Inc.

Inventor： Cicero NOGUEIRA DOS SANTOS ,  Xiaofei MA ,  Peng XU ,  Ramesh M. NALLAPATI ,  Bing XIANG ,  Sudipta SENGUPTA ,  Zhiguo WANG ,  Patrick NG

IPC: G06F16/9032 ,  G06N20/00 ,  G06F16/9038 ,  G06K9/62

Abstract: Techniques for generation of synthetic queries from customer data for training of document querying machine learning (ML) models as a service are described. A service may receive one or more documents from a user, generate a set of question and answer pairs from the one or more documents from the user using a machine learning model trained to predict a question from an answer, and store the set of question and answer pairs generated from the one or more documents from the user. The question and answer pairs may be used to train another machine learning model, for example, a document ranking model, a passage ranking model, a question/answer model, or a frequently asked question (FAQ) model.

公开(公告)号：US20210158209A1

公开(公告)日：2021-05-27

申请号：US16698027

申请日：2019-11-27

Applicant: Amazon Technologies, Inc.

Inventor： Bing XIANG ,  Jean-Pierre DODEL ,  Ramesh M. NALLAPATI

IPC: G06N20/00 ,  G06F16/93 ,  G06F16/9038 ,  G06F16/903

Abstract: Techniques for active learning for document querying machine learning (ML) models as a service are described. A service may perform a search of data of a user, using a machine learning model, for a search query to generate a result, generate a confidence score for the result of the search, select a proper subset of the data to be provided to the user based on the confidence score, display the proper subset of the data to the user, receive an indication from the user of one or more sections of the proper subset of the data for use in a next training iteration of the machine learning model, and perform the next training iteration of the machine learning model with the one or more sections of the proper subset of the data.

公开(公告)号：US20210157854A1

公开(公告)日：2021-05-27

申请号：US16697979

申请日：2019-11-27

Applicant: Amazon Technologies, Inc.

Inventor： Zhiguo WANG ,  Zhiheng HUANG ,  Ramesh M. NALLAPATI ,  Bing XIANG

IPC: G06F16/9038 ,  G06N20/00 ,  G06F16/93 ,  G06F16/908

Abstract: Techniques for displaying a search are described. An exemplary method includes receiving a search query, performing the search query on a plurality of documents, the documents including text passages, to generate a search query result, determining an aspect of the search query result that has a confidence value that exceeds a first confidence threshold with respect to its relevance to the search query; and, displaying the search result including an emphasis on the aspect of the result exceeds the first confidence threshold.