Details
| Original language | English |
|---|---|
| Title of host publication | Advanced Information Systems Engineering |
| Subtitle of host publication | 20th International Conference, CAiSE 2008, Proceedings |
| Pages | 556-570 |
| Number of pages | 15 |
| ISBN (electronic) | 978-3-540-69534-9 |
| Publication status | Published - 2008 |
| Event | 20th International Conference on Advanced Information Systems Engineering, CAiSE 2008 - Montpellier, France Duration: 16 Jun 2008 → 20 Jun 2008 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 5074 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (electronic) | 1611-3349 |
Abstract
Heterogeneous information spaces are typically created by merging data from a variety of different applications and information sources. These sources often use different identifiers for data that describe the same real-word entity (for example an artist, a conference, an organization). In this paper we propose a new probabilistic Entity Linkage algorithm for identifying and linking data that refer to the same real-world entity. Our approach focuses on managing entity linkage information in heterogeneous information spaces using probabilistic methods. We use a Bayesian network to model evidences which support the possible object matches along with the interdependencies between them. This enables us to flexibly update the network when new information becomes available, and to cope with the different requirements imposed by applications build on top of information spaces.
Keywords
- Data integration, Entity linkage, Metadata management
ASJC Scopus subject areas
- Mathematics(all)
- Theoretical Computer Science
- Computer Science(all)
Cite this
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Advanced Information Systems Engineering : 20th International Conference, CAiSE 2008, Proceedings. 2008. p. 556-570 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5074 LNCS).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Probabilistic entity linkage for heterogeneous information spaces
AU - Ioannou, Ekaterini
AU - Niederée, Claudia
AU - Nejdl, Wolfgang
PY - 2008
Y1 - 2008
N2 - Heterogeneous information spaces are typically created by merging data from a variety of different applications and information sources. These sources often use different identifiers for data that describe the same real-word entity (for example an artist, a conference, an organization). In this paper we propose a new probabilistic Entity Linkage algorithm for identifying and linking data that refer to the same real-world entity. Our approach focuses on managing entity linkage information in heterogeneous information spaces using probabilistic methods. We use a Bayesian network to model evidences which support the possible object matches along with the interdependencies between them. This enables us to flexibly update the network when new information becomes available, and to cope with the different requirements imposed by applications build on top of information spaces.
AB - Heterogeneous information spaces are typically created by merging data from a variety of different applications and information sources. These sources often use different identifiers for data that describe the same real-word entity (for example an artist, a conference, an organization). In this paper we propose a new probabilistic Entity Linkage algorithm for identifying and linking data that refer to the same real-world entity. Our approach focuses on managing entity linkage information in heterogeneous information spaces using probabilistic methods. We use a Bayesian network to model evidences which support the possible object matches along with the interdependencies between them. This enables us to flexibly update the network when new information becomes available, and to cope with the different requirements imposed by applications build on top of information spaces.
KW - Data integration
KW - Entity linkage
KW - Metadata management
UR - http://www.scopus.com/inward/record.url?scp=45849137843&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-69534-9_41
DO - 10.1007/978-3-540-69534-9_41
M3 - Conference contribution
AN - SCOPUS:45849137843
SN - 978-3-540-69533-2
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 556
EP - 570
BT - Advanced Information Systems Engineering
T2 - 20th International Conference on Advanced Information Systems Engineering, CAiSE 2008
Y2 - 16 June 2008 through 20 June 2008
ER -