Entity Matching Method and Apparatus

Patent metadata

Field	Value
Publication number	US-2016364366-A1
Application number	US-201615245795-A
Country	US
Kind code	A1
Filing date	Aug 24, 2016
Priority date	Feb 28, 2014
Publication date	Dec 15, 2016
Grant date	—

Abstract

An entity matching method and apparatus, where the method includes, calculating kernel matrices K and L after reading a first data source and a second data source with inconsistent entity quantities, respectively, solving a first optimization objective function to obtain a matrix M of a correspondence between an entity on the first data source and an entity on the second data source, and outputting the obtained matrix M. Hence, according to the entity matching method and apparatus provided in the present disclosure, entity matching when entity quantities of data sources are inconsistent may be performed such that accuracy of data mining may be effectively improved, and data value may be effectively presented.

First claim

What is claimed is:

1 . An entity matching method, comprising:
calculating an m 1 ×m 1 kernel matrix K on a first data source after reading the first data source; calculating an m 2 ×m 2 kernel matrix L on a second data source after reading the second data source, wherein entity quantities of the first data source and the second data source are respectively m 1 and m 2 ; solving a first optimization objective function to obtain a matrix M of a correspondence between an entity on the first data source and an entity on the second data source, wherein the first optimization objective function is

min
M



||

KM
T

-

(
LM
)

T



||
2





s
.
t





M
ij

∈

{

0
,
1

)



∀
i

,
j
,

M
T



1

m
2

≤

1

m
1

,

M




1

m
1

≤

1

m
2

,

and


(

1

m
2

)

T


M




1

m
1

=

min


(

m
1

,

m
2

)

,

wherein the matrix M is an m 2 ×m 1 matrix, wherein the M ij =1 indicates that a j th entity on the first data source matches an i th entity on the second data source, and wherein the M ij =0 indicates that the j th entity on the first data source does not match the i th entity on the second data source; and
outputting the obtained matrix M.

2 . The method according to claim 1 , wherein the first optimization objective function is

min
M



||

KM
T

-

(
LM
)

T



||
2





s
.
t





M
ij

≥

0




∀
i

,
j
,

M
T



1

m
2

≤

1

m
1

,

M




1

m
1

≤

1

m
2

Assignees

• Huawei Tech Co Ltd

Inventors

• Lan Liang
• Yuan Mingxuan
• Zeng Jia

Classifications

• G06F17/11 Primary

  for solving equations {, e.g. nonlinear equations, general mathematical optimization problems (optimization specially adapted for a specific administrative, business or logistic context G06Q10/04)} · CPC title

• G06F17/16 Primary

  Matrix or vector computation {, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization (matrix transposition G06F7/78)} · CPC title

• G06F18/22

  Matching criteria, e.g. proximity measures · CPC title