• Publications
  • Influence
Learning to map between ontologies on the semantic web
Ontologies play a prominent role on the Semantic Web. They make possible the widespread publication of machine understandable data, opening myriad opportunities for automated information processing.Expand
  • 1,050
  • 72
Reconciling schemas of disparate data sources: a machine-learning approach
A data-integration system provides access to a multitude of data sources through a single mediated schema. A key bottleneck in building such systems has been the laborious manual construction ofExpand
  • 874
  • 57
Tuffy: Scaling up Statistical Inference in Markov Logic Networks using an RDBMS
Markov Logic Networks (MLNs) have emerged as a powerful framework that combines statistical and logical reasoning; they have been applied to many data intensive problems including informationExpand
  • 263
  • 47
Learning to match ontologies on the Semantic Web
Abstract.On the Semantic Web, data will inevitably come from many different ontologies, and information processing across ontologies is not possible without knowing the semantic mappings betweenExpand
  • 529
  • 33
Ontology Matching: A Machine Learning Approach
This chapter studies ontology matching: the problem of finding the semantic mappings between two given ontologies. This problem lies at the heart of numerous information processing applications.Expand
  • 511
  • 32
Deep Learning for Entity Matching: A Design Space Exploration
Entity matching (EM) finds data instances that refer to the same real-world entity. In this paper we examine applying deep learning (DL) to EM, to understand DL's benefits and limitations. We reviewExpand
  • 113
  • 28
iMAP: discovering complex semantic matches between database schemas
Creating semantic matches between disparate data sources is fundamental to numerous data sharing efforts. Manually creating matches is extremely tedious and error-prone. Hence many recent works haveExpand
  • 421
  • 27
Principles of Data Integration
How do you approach answering queries when your data is stored in multiple databases that were designed independently by different people? This is first comprehensive book on data integration and isExpand
  • 389
  • 26
An interactive clustering-based approach to integrating source query interfaces on the deep Web
An increasing number of data sources now become available on the Web, but often their contents are only accessible through query interfaces. For a domain of interest, there often exist many suchExpand
  • 286
  • 24
Corleone: hands-off crowdsourcing for entity matching
Recent approaches to crowdsourcing entity matching (EM) are limited in that they crowdsource only parts of the EM workflow, requiring a developer to execute the remaining parts. Consequently, theseExpand
  • 181
  • 22