Schema Matching and Mapping
By Zohra Bellahsene, A. Bonifati, Erhard Rahm. Schema Matching and Mapping, 2013
377 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Networks and Communications, Information Systems
View Paper: https://www.semanticscholar.org/paper/c1e99ca6a039176d530576f220d9fae34a668ba3
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Pavel Shvaiko
- Jérôme Euzenat
- Peter Christen
- Erhard Rahm
- Heiko Paulheim
- Philip A. Bernstein
- Jayant Madhavan
- Xin Luna Dong
In Computer Networks and Communications
- Pavel Shvaiko
- Jérôme Euzenat
- Jayant Madhavan
- Peter Christen
- Philip A. Bernstein
- Erhard Rahm
- Xin Luna Dong
- Dinusha Vatsalan
In Information Systems
- Pavel Shvaiko
- Jérôme Euzenat
- Heiko Paulheim
- Peter Christen
- Dinusha Vatsalan
- Vassilios S. Verykios
- Philip A. Bernstein
- Jayant Madhavan
Citations in the corpus
- Ontology Matching: State of the Art and Future Challenges (2013, background): “Several recent surveys [10–16] and books [2, 7] have been written on the topic 1 as well.”
- InfoGather: entity augmentation and attribute discovery by holistic matching with web tables (2012, methodology): “The baseline technique first identifies web tables that semantically “matches” with the query table using schema matching techniques (we consider simple 1:1 mappings only) [2].”
- Big data integration (2013, background): “…[32] Schema mapping in a data integration system refers to (i) creating a mediated (global) schema, and (ii) identifying the mappings between the mediated (global) schema and the local schemas of the data sources to determine which (sets of) attributes contain the same information [41], [3], [1].”
- A taxonomy of privacy-preserving record linkage techniques (2013, background): “The three major tasks in data integration are schema matching [9], record linkage [6,10], and data fusion [11,12].”
- Generic schema matching, ten years later (2011, background): “There are now two books on schema matching [5][26] and two surveys [63][68], so there is little point in our repeating such a survey.”
- Data Matching (2012, background): “This process is highly significant, for example, for company mergers, collaborative e-Commerce projects, data mash-ups and scientific collaborations [24].”
- Unsupervised generation of data mining features from linked open data (2012, background): “Therefore, we refer to a number of survey articles summarizing the state of the art in ontology learning [10, 18, 32] and ontology matching [2, 11], respectively.”