Duplicate Detection in Probabilistic Data

Fabian Panse; Maurice van Keulen; Ander de Keijzer; Norbert Ritter

doi:10.1109/ICDEW.2010.5452759

Duplicate Detection in Probabilistic Data

Fabian Panse, Maurice van Keulen, Ander de Keijzer, Norbert Ritter

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

16 Citations (Scopus)

253 Downloads (Pure)

Abstract

Collected data often contains uncertainties. Probabilistic databases have been proposed to manage uncertain data. To combine data from multiple autonomous probabilistic databases, an integration of probabilistic data has to be performed. Until now, however, data integration approaches have focused on the integration of certain source data (relational or XML). There is no work on the integration of uncertain source data so far. In this paper, we present a first step towards a concise consolidation of probabilistic data. We focus on duplicate detection as a representative and essential step in an integration process. We present techniques for identifying multiple probabilistic representations of the same real-world entities.

Original language	Undefined
Title of host publication	Proceedings of the 2nd International Workshop on New Trends in Information Integration (NTII 2010)
Place of Publication	Los Alamitos
Publisher	IEEE
Pages	179-182
Number of pages	6
ISBN (Print)	978-1-4244-6522-4
DOIs	https://doi.org/10.1109/ICDEW.2010.5452759
Publication status	Published - Mar 2010
Event	2nd International Workshop on New Trends in Information Integration (NTII 2010), Long Beach, California, USA: Proceedings of the 2nd International Workshop on New Trends in Information Integration (NTII 2010) - Los Alamitos Duration: 1 Mar 2010 → …

Publication series

Name
Publisher	IEEE Computer Society Press

Conference

Conference	2nd International Workshop on New Trends in Information Integration (NTII 2010), Long Beach, California, USA
City	Los Alamitos
Period	1/03/10 → …

Keywords

IR-68597
EWI-16565
DB-SDI: SCHEMA AND DATA INTEGRATION
METIS-270698

Access to Document

10.1109/ICDEW.2010.5452759

Cite this

@inproceedings{be63fa7152be42d2b3b3fb7ce7dc8df4,

title = "Duplicate Detection in Probabilistic Data",

abstract = "Collected data often contains uncertainties. Probabilistic databases have been proposed to manage uncertain data. To combine data from multiple autonomous probabilistic databases, an integration of probabilistic data has to be performed. Until now, however, data integration approaches have focused on the integration of certain source data (relational or XML). There is no work on the integration of uncertain source data so far. In this paper, we present a first step towards a concise consolidation of probabilistic data. We focus on duplicate detection as a representative and essential step in an integration process. We present techniques for identifying multiple probabilistic representations of the same real-world entities.",

keywords = "IR-68597, EWI-16565, DB-SDI: SCHEMA AND DATA INTEGRATION, METIS-270698",

author = "Fabian Panse and {van Keulen}, Maurice and {de Keijzer}, Ander and Norbert Ritter",

note = "10.1109/ICDEW.2010.5452759 ; null ; Conference date: 01-03-2010",

year = "2010",

month = mar,

doi = "10.1109/ICDEW.2010.5452759",

language = "Undefined",

isbn = "978-1-4244-6522-4",

publisher = "IEEE",

pages = "179--182",

booktitle = "Proceedings of the 2nd International Workshop on New Trends in Information Integration (NTII 2010)",

}

Panse, F, van Keulen, M, de Keijzer, A & Ritter, N 2010, Duplicate Detection in Probabilistic Data. in Proceedings of the 2nd International Workshop on New Trends in Information Integration (NTII 2010). IEEE, Los Alamitos, pp. 179-182, 2nd International Workshop on New Trends in Information Integration (NTII 2010), Long Beach, California, USA, Los Alamitos, 1/03/10. https://doi.org/10.1109/ICDEW.2010.5452759

TY - GEN

T1 - Duplicate Detection in Probabilistic Data

AU - Panse, Fabian

AU - van Keulen, Maurice

AU - de Keijzer, Ander

AU - Ritter, Norbert

N1 - 10.1109/ICDEW.2010.5452759

PY - 2010/3

Y1 - 2010/3

N2 - Collected data often contains uncertainties. Probabilistic databases have been proposed to manage uncertain data. To combine data from multiple autonomous probabilistic databases, an integration of probabilistic data has to be performed. Until now, however, data integration approaches have focused on the integration of certain source data (relational or XML). There is no work on the integration of uncertain source data so far. In this paper, we present a first step towards a concise consolidation of probabilistic data. We focus on duplicate detection as a representative and essential step in an integration process. We present techniques for identifying multiple probabilistic representations of the same real-world entities.

AB - Collected data often contains uncertainties. Probabilistic databases have been proposed to manage uncertain data. To combine data from multiple autonomous probabilistic databases, an integration of probabilistic data has to be performed. Until now, however, data integration approaches have focused on the integration of certain source data (relational or XML). There is no work on the integration of uncertain source data so far. In this paper, we present a first step towards a concise consolidation of probabilistic data. We focus on duplicate detection as a representative and essential step in an integration process. We present techniques for identifying multiple probabilistic representations of the same real-world entities.

KW - IR-68597

KW - EWI-16565

KW - DB-SDI: SCHEMA AND DATA INTEGRATION

KW - METIS-270698

U2 - 10.1109/ICDEW.2010.5452759

DO - 10.1109/ICDEW.2010.5452759

M3 - Conference contribution

SN - 978-1-4244-6522-4

SP - 179

EP - 182

BT - Proceedings of the 2nd International Workshop on New Trends in Information Integration (NTII 2010)

PB - IEEE

CY - Los Alamitos

Y2 - 1 March 2010

ER -