Semantic integration of heterogeneous information sources
Data & Knowledge Engineering - Special issue on heterogeneous information resources need semantic access
Data integration: a theoretical perspective
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
Schema and ontology matching with COMA++
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Yago: a core of semantic knowledge
Proceedings of the 16th international conference on World Wide Web
Iterative Set Expansion of Named Entities Using the Web
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
RDFKB: efficient support for RDF inference queries and knowledge management
IDEAS '09 Proceedings of the 2009 International Database Engineering & Applications Symposium
Google fusion tables: data management, integration and collaboration in the cloud
Proceedings of the 1st ACM symposium on Cloud computing
Entity discovery and annotation in tables
Proceedings of the 16th International Conference on Extending Database Technology
Scalable column concept determination for web tables using large knowledge bases
Proceedings of the VLDB Endowment
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Many RDF Knowledge Bases are created and enlarged by mining and extracting web data. Hence their data sources are limited to social tagging networks, such as Wikipedia, WordNet, IMDB, etc., and their precision is not guaranteed. In this paper, we propose a new system, ITEM, for extracting and integrating entities from tabular data to RDF knowledge base. ITEM can efficiently compute the schema mapping between a table and a KB, and inject novel entities into the KB. Therefore, ITEM can enlarge and improve RDF KB by employing tabular data, which is assumed of high quality. ITEM detects the schema mapping between table and RDF KB only by tuples, rather than the table's schema information. Experimental results show that our system has high precision and good performance.