S
Sergey Melnik
Researcher at Microsoft
Publications - 52
Citations - 6349
Sergey Melnik is an academic researcher from Microsoft. The author has contributed to research in topics: Schema matching & Database schema. The author has an hindex of 32, co-authored 51 publications receiving 6217 citations. Previous affiliations of Sergey Melnik include University of Limerick & Stanford University.
Papers
More filters
Proceedings ArticleDOI
Similarity flooding: a versatile graph matching algorithm and its application to schema matching
TL;DR: This paper presents a matching algorithm based on a fixpoint computation that is usable across different scenarios and conducts a user study, in which the accuracy metric was used to estimate the labor savings that the users could obtain by utilizing the algorithm to obtain an initial matching.
Journal ArticleDOI
The Semantic Web: the roles of XML and RDF
Stefan Decker,Sergey Melnik,F.A.H. van Harmelen,Dieter Fensel,Michel C. A. Klein,Jeen Broekstra,Michael Erdmann,Ian Horrocks +7 more
TL;DR: It is argued that a further representation and inference layer is needed on top of the Web's current layers, and to establish such a layer, a general method for encoding ontology representation languages into RDF/RDF schema is proposed.
Book ChapterDOI
Comparison of Schema Matching Evaluations
TL;DR: In this article, the authors survey recently published schema matching evaluations and compare the effectiveness of different schema matching approaches, based on their observations, they discuss the requirements for future schema matching implementations and evaluations.
Proceedings ArticleDOI
Model management 2.0: manipulating richer mappings
TL;DR: A revised vision that differs from the original in two main respects: the operations must handle more expressive mappings, and the runtime that executes mappings should be added as an important model management component.
Proceedings ArticleDOI
Rondo: a programming platform for generic model management
TL;DR: This work presents a first complete prototype of a generic model management system, in which high-level operators are used to manipulate models and mappings between models, and defines the key conceptual structures: models, morphisms, and selectors.