Clean Answers over Dirty Databases: A Probabilistic Approach
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Principles of dataspace systems
Proceedings of the twenty-fifth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Trio: a system for data, uncertainty, and lineage
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Duplicate Record Detection: A Survey
IEEE Transactions on Knowledge and Data Engineering
Probabilistic Entity Linkage for Heterogeneous Information Spaces
CAiSE '08 Proceedings of the 20th international conference on Advanced Information Systems Engineering
On-the-fly entity-aware query processing in the presence of linkage
Proceedings of the VLDB Endowment
Chronos: facilitating history discovery by linking temporal records
Proceedings of the VLDB Endowment
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Entity linkage deals with the problem of identifying whether two pieces of information represent the same real world object. The traditional methodology computes the similarity among the entities, and then merges those with similarity above some specific threshold. We demonstrate LinkDB, an original entity storage and querying system that deals with the entity linkage problem in a novel way. LinkDB is a probabilistic linkage database that uses existing linkage techniques to generate linkages among entities, but instead of performing the merges based on these linkages, it stores them alongside the data and performs only the required merges at run-time, by effectively taking into consideration the query specifications. We explain the technical challenges behind this kind of query answering, and we show how this new mechanism is able to provide answers that traditional entity linkage mechanisms cannot.