Ontology guided data linkage framework for discovering meaningful data facts

Mohammed Gollapalli; Xue Li; Ian Wood; Guido Governatori

doi:10.1007/978-3-642-25856-5_19

Ontology guided data linkage framework for discovering meaningful data facts

Mohammed Gollapalli, Xue Li, Ian Wood, Guido Governatori

Artificial Intelligence and Cyber Futures Institute

University of Queensland

Research output: Book chapter/Published conference paper › Conference paper › peer-review

9 Citations (Scopus)

Abstract

Making sensible queries on databases collected from different organizations presents a challenging task for linking semantic equivalent data facts. Current techniques primarily focused on performing pair-wise attribute matching and paid little attention towards discovering probabilistic structural dependencies by exploiting the ontological domain knowledge of tables, attributes and tuples to construct hierarchical cluster mapping trees. In this paper, we present Ontology Guided Data Linkage (OGDL) framework for self-organizing heterogeneous data sources into homogeneous ontological clusters through multi-faceted classification. Through the evaluation on real-world data, we demonstrate the robustness and accuracy of our system.

Original language	English
Title of host publication	Advanced Data Mining and Applications - 7th International Conference, ADMA 2011, Proceedings
Pages	252-265
Number of pages	14
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-642-25856-5_19
Publication status	Published - 2011
Event	7th International Conference on Advanced Data Mining and Applications, ADMA 2011 - Beijing, China Duration: 17 Dec 2011 → 19 Dec 2011

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	7121 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	7th International Conference on Advanced Data Mining and Applications, ADMA 2011
Country/Territory	China
City	Beijing
Period	17/12/11 → 19/12/11

Access to Document

10.1007/978-3-642-25856-5_19

Cite this

Gollapalli, M., Li, X., Wood, I., & Governatori, G. (2011). Ontology guided data linkage framework for discovering meaningful data facts. In Advanced Data Mining and Applications - 7th International Conference, ADMA 2011, Proceedings (PART 2 ed., pp. 252-265). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7121 LNAI, No. PART 2). https://doi.org/10.1007/978-3-642-25856-5_19

Gollapalli, Mohammed ; Li, Xue ; Wood, Ian et al. / Ontology guided data linkage framework for discovering meaningful data facts. Advanced Data Mining and Applications - 7th International Conference, ADMA 2011, Proceedings. PART 2. ed. 2011. pp. 252-265 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

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abstract = "Making sensible queries on databases collected from different organizations presents a challenging task for linking semantic equivalent data facts. Current techniques primarily focused on performing pair-wise attribute matching and paid little attention towards discovering probabilistic structural dependencies by exploiting the ontological domain knowledge of tables, attributes and tuples to construct hierarchical cluster mapping trees. In this paper, we present Ontology Guided Data Linkage (OGDL) framework for self-organizing heterogeneous data sources into homogeneous ontological clusters through multi-faceted classification. Through the evaluation on real-world data, we demonstrate the robustness and accuracy of our system.",

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Gollapalli, M, Li, X, Wood, I & Governatori, G 2011, Ontology guided data linkage framework for discovering meaningful data facts. in Advanced Data Mining and Applications - 7th International Conference, ADMA 2011, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 7121 LNAI, pp. 252-265, 7th International Conference on Advanced Data Mining and Applications, ADMA 2011, Beijing, China, 17/12/11. https://doi.org/10.1007/978-3-642-25856-5_19

Ontology guided data linkage framework for discovering meaningful data facts. / Gollapalli, Mohammed; Li, Xue; Wood, Ian et al.
Advanced Data Mining and Applications - 7th International Conference, ADMA 2011, Proceedings. PART 2. ed. 2011. p. 252-265 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7121 LNAI, No. PART 2).

Research output: Book chapter/Published conference paper › Conference paper › peer-review

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Gollapalli M, Li X, Wood I, Governatori G. Ontology guided data linkage framework for discovering meaningful data facts. In Advanced Data Mining and Applications - 7th International Conference, ADMA 2011, Proceedings. PART 2 ed. 2011. p. 252-265. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-25856-5_19

Ontology guided data linkage framework for discovering meaningful data facts

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