Ontology-Based Integration of Information - A Survey of Existing Approaches

By H. Wache, T. Vögele, Ubbo Visser, Heiner Stuckenschmidt, G. Schuster, H. Neumann, S. Hübner. OIS@IJCAI, 2001

1,489 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/e24d50aec62d6968e3b0b6cac203dc5ea335710d

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Citations in the corpus

A Survey of Schema-Based Matching Approaches (2005, unknown): “The survey of [52] concentrates on approaches to ontology-based information integration and discusses general matching approaches that are used in information integration systems.”
An innovative web-based collaborative platform for video annotation (2013, methodology): “Machine learning methods [26, 28, 44] will be applied on these textual annotations in order to exploit the advantages offered by integrating annotations to multiple types and levels of information.”
Metamodelling Platforms (2002, background): “In addition to technical integrations, the systems have to be integrated on a semantically level [25].”
A theoretical framework for learning from a pool of disparate data sources (2002, background): “We should point out the distinction between our notion of "data integration" and the concept of "data fusion," on which there is an abundance of literature [7, 15, 16].”
Multisensor data fusion: A review of the state-of-the-art (2013, background): “While several general [1] [2] [3] and specific [4] [5] [6] [7] [8] reviews of the data fusion literature exist; this paper is intended to provide the reader with a generic and comprehensive view of contemporary data fusion methodologies, as well as the most recent developments and emerging trends…”
RiMOM: A Dynamic Multistrategy Ontology Alignment Framework (2009, background): “There are several surveys on schema matching and ontology alignment [18], [22], [23], [31], [55], [57], [61].”
Subspace clustering for high dimensional data: a review (2004, background): “That is when a keyword in one domain holds a different meaning in another domain making information sharing and interoperability between heterogeneous systems difficult [72].”
Opinion Mining and Information Fusion: A survey (2016, background): “[151] in which the authors review the use of ontologies for the fusion of data issued from different sources.”
Semantic similarity methods in wordNet and their application to information retrieval on the web (2005, background): “Accordingly, different approaches for comparing concepts within or across ontologies can be defined [54].”
Ontology Matching (2007, background): “There have been many different classifications to types of heterogeneity (Batini et al. 1986; Sheth and Larson 1990; Breitbart 1990; Kim and Seo 1991; Goh 1997; Hull 1997; Kashyap and Sheth 1998; Benerecetti et al. 2000; Wache et al. 2001; Klein 2001; Euzenat 2001; Corcho 2005; Hameed et al. 2004; G”
Adding Semantics to Web Services Standards (2003, background): “Use of ontologies to provide underpinning for information sharing and semantic interoperability has been long realized [6, 7, 8].”