International audienceThis paper presents an efficient approach to query big RDF data sources in order to get more relevant and complete results. The approach deals with two important heterogeneities in huge amount of data: semantic and URI-based entity identification heterogeneities. The paper proposes: (1) a semantic entity resolution approach based on inference mechanism to manage ambiguity of real world entities for linking data at the semantic and URI levels (2) a MapReduce-based query rewriting approach based on entity resolution results to include implicit data into query results (3) algorithms based on MapReduce paradigm to deal with huge amounts of data
Summarization: The web of data consists of distributed, diverse (in terms of schema adopted), and la...
Entity Resolution (ER) lies at the core of data integration, with a bulk of research focusing on its...
The proliferation of heterogeneous data sources in many application contexts brings an urgent need f...
International audienceThe number of linked data sources and the size of the linked open data graph k...
Abstract. In order to lay a solid foundation for the emerging semantic web, effective and efficient ...
AbstractProcessing massive RDF data complicated query efficiently is a matter of concern for a long ...
As more and more data is provided in RDF format, storing huge amounts of RDF data and efficiently pr...
As more and more data is provided in RDF format, storing huge amounts of RDF data and efficiently pr...
Abstract — Reasoning on a Web scale becomes increasingly challenging because of the large volume of ...
Entity Resolution (ER) concerns identifying logically equivalent pairs of entities that may be synta...
Abstract. Increasing availability of RDF data covering different domains is en-abling ad-hoc integra...
The Semantic Web, or the Web of Data, promotes common data formats for representing structured data ...
Entity disambiguation is the task of mapping ambiguous terms in natural-language text to its entitie...
Triple stores have long provided RDF storage as well as data access using expressive, formal query l...
With respect to large-scale, static, Linked Data corpora, in this paper we discuss scalable and dist...
Summarization: The web of data consists of distributed, diverse (in terms of schema adopted), and la...
Entity Resolution (ER) lies at the core of data integration, with a bulk of research focusing on its...
The proliferation of heterogeneous data sources in many application contexts brings an urgent need f...
International audienceThe number of linked data sources and the size of the linked open data graph k...
Abstract. In order to lay a solid foundation for the emerging semantic web, effective and efficient ...
AbstractProcessing massive RDF data complicated query efficiently is a matter of concern for a long ...
As more and more data is provided in RDF format, storing huge amounts of RDF data and efficiently pr...
As more and more data is provided in RDF format, storing huge amounts of RDF data and efficiently pr...
Abstract — Reasoning on a Web scale becomes increasingly challenging because of the large volume of ...
Entity Resolution (ER) concerns identifying logically equivalent pairs of entities that may be synta...
Abstract. Increasing availability of RDF data covering different domains is en-abling ad-hoc integra...
The Semantic Web, or the Web of Data, promotes common data formats for representing structured data ...
Entity disambiguation is the task of mapping ambiguous terms in natural-language text to its entitie...
Triple stores have long provided RDF storage as well as data access using expressive, formal query l...
With respect to large-scale, static, Linked Data corpora, in this paper we discuss scalable and dist...
Summarization: The web of data consists of distributed, diverse (in terms of schema adopted), and la...
Entity Resolution (ER) lies at the core of data integration, with a bulk of research focusing on its...
The proliferation of heterogeneous data sources in many application contexts brings an urgent need f...