Evaluation of entity resolution approaches on real-world

Evaluation of entity resolution approaches on real-world

Cached

Download Links

by Hanna Köpcke , Andreas Thor , Erhard Rahm

Citations:

BibTeX

@MISC{Köpcke_evaluationof,
    author = {Hanna Köpcke and Andreas Thor and Erhard Rahm},
    title = {Evaluation of entity resolution approaches on real-world},
    year = {}
}

Bookmark

OpenURL

Abstract

match problems

Citations

311	A theory for record linkage - Fellegi, Sunter - 1969
254	Merge/Purge Problem for Large Databases - Hernandez, Stolfo - 1995
200	Efficient clustering of high-dimensional data sets with application to reference matching - McCallum, Nigam, et al. - 2000
132	Data cleaning: Problems and current approaches - Rahm, Do - 2000
56	TAILOR: A record linkage tool box - Elfeky, Elmagarmid, et al. - 2002
32	J.X.: Efficient Similarity Joins for Near Duplicate Detection - Xiao, Wang, et al. - 2008
30	DogmatiX tracks down duplicates in XML - Weis, Naumann - 2005
29	Object identification with attribute-mediated dependences - Singla, Domingos - 2005
21	Learning blocking schemes for record linkage - Michelson, Knoblock - 2006
19	E.: MOMA - a mapping-based object matching system - Thor, Rahm - 2007
12	E.: Frameworks for entity matching: A comparison - Köpcke, Rahm - 2010
10	L.: Link-based classification using labeled and unlabeled data. In: Workshop on the continuum from labeled to unlabeled data, ICML - Lu, Getoor - 2003
9	Decision Models for Record Linkage - Gu, Baxter
8	Comparative evaluation of entity resolution approaches with fever - Köpcke, Thor, et al.
7	Object identification quality - Neiling, Jurk, et al. - 2003
6	Framework for evaluating clustering algorithms in duplicate detection - Hassanzadeh, Chiang, et al. - 2009
6	E.: Learning-Based Approaches for Matching Web Data Entities - Köpcke, Thor, et al. - 2010
4	E.: Training Selection for Tuning Entity Matching - Köpcke, Rahm - 2008
3	A Duplicate Detection Benchmark for XML (and Relational) Data - Weis, Naumann, et al.
1	M.: SimEval: a tool for evaluating the quality of similarity functions - Heuser, Krieser, et al.