Entity Resolution (Entity Resolution)

Description

Entity resolution (ER) is the problem of matching records that represent the same real-world entity and then merging the matching records. ER is a well known problem that arises in many applications. An exhaustive ER process involves comparing all the pairs of records, which can be very expensive for large datasets.

Parameters

$n$: number of records

$k$: number of features

Table of Algorithms

Name	Year	Time	Space	Approximation Factor	Model	Reference
Fellegi & Sunter Model	1969	$O(n^{3}k)$	$O(k)$	Exact	Deterministic	Time
Gupta & Sarawagi CRF	2009	$O(n^{3}k)$	$O(nk)$?	Exact	Deterministic	Time
Chen Ensembles of classifiers	1989	$O(n^{2} \log n)$		Exact	Deterministic
EM Based Winkler	2000	$O(n^{3}k)$	$O(k)$	Exact	Deterministic	Time
Ravikumar & Cohen Generative Models	2004	$O(n^{2} k)$	$O(k)$	Exact	Deterministic	Time
Bellare Active Learning	2012	$O(n^{2} \log n c \log c)$		Exact	Deterministic	Time
Ananthakrishna	2002	$O(n^{2} k)$	$O(n)$	Exact	Deterministic	Time
BOYS algorithm	1993	$O(n^{2} k)$	$O(n^{2})$	Exact	Deterministic	Time

Time Complexity Graph

Space Complexity Graph

Time-Space Tradeoff