公开(公告)号：US20200034740A1

公开(公告)日：2020-01-30

申请号：US16587977

申请日：2019-09-30

Applicant: Alibaba Group Holding Limited

Inventor： Xinxing Yang ,  Shaosheng Cao ,  Jun Zhou ,  Xiaolong Li

IPC: G06N20/00 ,  G06F17/16 ,  G06F17/18 ,  G06K9/62

Abstract: An N×M dimensional target matrix is generated based on N data samples and M dimensional data features respectively corresponding to the N data samples. Encryption calculation is performed on the N×M dimensional target matrix based on a Principal Component Analysis (PCA) algorithm to obtain an N×K dimensional encryption matrix K is less than M. The N×K dimensional encryption matrix is transmitted to a modeling server. The modeling server trains a machine learning model by using the N×K dimensional encryption matrix as a training sample.

公开(公告)号：US20190034937A1

公开(公告)日：2019-01-31

申请号：US16146241

申请日：2018-09-28

Applicant: Alibaba Group Holding Limited

Inventor： Jiaxing Zhang ,  Hengbin Cui ,  Shaofei Xue ,  Xiaolong Li

IPC: G06Q30/00 ,  G06N5/02

Abstract: Problem prediction method and system are provided. The prediction method includes receiving a request sent by a client, and obtaining a track of user activities of the client, the track of user activities including at least one of: call information of at least one RPC between the client and a server in a specified time period, or at least one URL of the server accessed by the client; extracting model input data from the track of user activities; and inputting the model input data into a problem classification model to predict a problem. The present disclosure uses a problem classification model to predict a problem, extracts model input data from a track of user activities as features for predicting the problem. In a process of prediction of a problem, manual operations are reduced, and the accuracy of the prediction is improved, while the timeliness is guaranteed at the same time.

公开(公告)号：US20180210876A1

公开(公告)日：2018-07-26

申请号：US15874725

申请日：2018-01-18

Applicant: Alibaba Group Holding Limited

Inventor： Shaosheng Cao ,  Xiaolong Li

IPC: G06F17/27 ,  G06N99/00

CPC classification number: G06F17/2785 ,  G06F17/2863 ,  G06N3/084 ,  G06N20/00

Abstract: A word vector processing method is provided. Word segmentation is performed on a corpus to obtain words, and n-gram strokes corresponding to the words are determined. Each n-gram stroke represents n successive strokes of a corresponding word. Word vectors of the words and stroke vectors of the n-gram strokes are initialized corresponding to the words. After performing the word segmentation, the n-gram strokes are determined, and the word vectors and stroke vectors are determined, training the word vectors and the stroke vectors.