Learning to map between ontologies on the semantic web
Proceedings of the 11th international conference on World Wide Web
A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
Schema Matching Using Duplicates
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Ontology Matching
Yago: a core of semantic knowledge
Proceedings of the 16th international conference on World Wide Web
Query relaxation using malleable schemas
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
COMA: a system for flexible combination of schema matching approaches
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Freebase: a collaboratively created graph database for structuring human knowledge
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Introduction to Information Retrieval
Introduction to Information Retrieval
YAGO-QA: Answering Questions by Structured Knowledge Queries
ICSC '11 Proceedings of the 2011 IEEE Fifth International Conference on Semantic Computing
PARIS: probabilistic alignment of relations, instances, and schema
Proceedings of the VLDB Endowment
FreeQ: an interactive query interface for freebase
Proceedings of the 21st international conference companion on World Wide Web
Efficient query construction for large scale data
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
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Linked Open Data (LOD) has emerged as the de-facto standard for publishing data on the Web. The cross-domain large scale Freebase and YAGO datasets represent central hubs and reference points for the LOD cloud. Freebase is an open-world dataset, which contains about 22 million entities and more than 350 million facts in more than 100 domains. The scale of Freebase makes it difficult for the users to get an overview of the data and efficiently retrieve the desired information. Integration of Freebase with the YAGO ontology that contains more than 360,000 concepts enables us to provide more semantic information for Freebase and to facilitate novel applications, such as efficient query construction, over large scale data. In this paper we analyze the structure of YAGO in more depth and show how to match YAGO and Freebase categories. The new YAGO+F structure that results from our matching tightly connects both datasets and provides an important next step to systematically interconnect LOD subcollections. We make our YAGO+F structure available online in the hope that it can provide a good starting point for future applications, which can build upon a wide variety of Freebase data clearly arranged in the semantic categories of YAGO.