Effective and Efficient Entity Search in RDF dataRoi Blanco
Triple stores have long provided RDF storage as well as data access using expressive, formal query languages such as SPARQL. The new end users of the Semantic Web, however, are mostly unaware of SPARQL and overwhelmingly prefer imprecise, informal keyword queries for searching over data. At the same time, the amount of data on the Semantic Web is approaching the limits of the architectures that provide support for the full expressivity of SPARQL. These factors combined have led to an increased interest in semantic search, i.e. access to RDF data using Information Retrieval methods. In this work, we propose a method for effective and efficient entity search over RDF data. We describe an adaptation of the BM25F ranking function for RDF data, and demonstrate that it outperforms other state-of-the-art methods in ranking RDF resources. We also propose a set of new index structures for efficient retrieval and ranking of results. We implement these results using the open-source MG4J framework.
Effective and Efficient Entity Search in RDF dataRoi Blanco
Triple stores have long provided RDF storage as well as data access using expressive, formal query languages such as SPARQL. The new end users of the Semantic Web, however, are mostly unaware of SPARQL and overwhelmingly prefer imprecise, informal keyword queries for searching over data. At the same time, the amount of data on the Semantic Web is approaching the limits of the architectures that provide support for the full expressivity of SPARQL. These factors combined have led to an increased interest in semantic search, i.e. access to RDF data using Information Retrieval methods. In this work, we propose a method for effective and efficient entity search over RDF data. We describe an adaptation of the BM25F ranking function for RDF data, and demonstrate that it outperforms other state-of-the-art methods in ranking RDF resources. We also propose a set of new index structures for efficient retrieval and ranking of results. We implement these results using the open-source MG4J framework.
Entity Linking via Graph-Distance MinimizationRoi Blanco
Entity-linking is a natural-language--processing task that consists in identifying strings of text that refer to a particular
item in some reference knowledge base.
One instance of entity-linking can be formalized as an optimization problem on the underlying concept graph, where the quantity to be optimized is the average distance between chosen items.
Inspired by this application, we define a new graph problem which is a natural variant of the Maximum Capacity Representative Set. We prove that our problem is NP-hard for general graphs; nonetheless, it turns out to be solvable in linear time under some more restrictive assumptions. For the general case, we propose several heuristics: one of these tries to enforce the above assumptions while the others try to optimize similar easier objective functions; we show experimentally how these approaches perform with respect to some baselines on a real-world dataset.
#ForoEGovAR | Plan de Modernización del EstadoCESSI ArgenTIna
Documento presentado por Andrés Ibarra, Ministro de Modernización de la Nación, en el Foro Argentino de Transformación Digital, organizado por CESSI y la United Nations University (UNU_EGOV). Buenos Aires, 7 de marzo de 2016.
#ForoEGovAR | Plataforma UNKSOC.ORG y Desarrollo de la ComunidadCESSI ArgenTIna
Documento elaborado por Joao A. Carvalho, Tomasz Janowski y Elsa Estevez con motivo del Foro Argentino de Transformación Digital, organizado por CESSI y la United Nations University (UNU_EGOV). Buenos Aires, 7 de marzo de 2016.
Greater Halifax Partnership: A Catalyst for Economic GrowthHalifax Partnership
The Greater Halifax Partnership is a catalyst for economic growth and confidence in Greater Halifax, the economic hub of Atlantic Canada.
We have deep insight into the city’s emerging trends and changing needs because of committed involvement and unequalled private sector investment, and government support. Staying one step ahead of opportunities and issues, we mobilize resources to accelerate the economic growth of Greater Halifax.
Entity Linking via Graph-Distance MinimizationRoi Blanco
Entity-linking is a natural-language--processing task that consists in identifying strings of text that refer to a particular
item in some reference knowledge base.
One instance of entity-linking can be formalized as an optimization problem on the underlying concept graph, where the quantity to be optimized is the average distance between chosen items.
Inspired by this application, we define a new graph problem which is a natural variant of the Maximum Capacity Representative Set. We prove that our problem is NP-hard for general graphs; nonetheless, it turns out to be solvable in linear time under some more restrictive assumptions. For the general case, we propose several heuristics: one of these tries to enforce the above assumptions while the others try to optimize similar easier objective functions; we show experimentally how these approaches perform with respect to some baselines on a real-world dataset.
#ForoEGovAR | Plan de Modernización del EstadoCESSI ArgenTIna
Documento presentado por Andrés Ibarra, Ministro de Modernización de la Nación, en el Foro Argentino de Transformación Digital, organizado por CESSI y la United Nations University (UNU_EGOV). Buenos Aires, 7 de marzo de 2016.
#ForoEGovAR | Plataforma UNKSOC.ORG y Desarrollo de la ComunidadCESSI ArgenTIna
Documento elaborado por Joao A. Carvalho, Tomasz Janowski y Elsa Estevez con motivo del Foro Argentino de Transformación Digital, organizado por CESSI y la United Nations University (UNU_EGOV). Buenos Aires, 7 de marzo de 2016.
Greater Halifax Partnership: A Catalyst for Economic GrowthHalifax Partnership
The Greater Halifax Partnership is a catalyst for economic growth and confidence in Greater Halifax, the economic hub of Atlantic Canada.
We have deep insight into the city’s emerging trends and changing needs because of committed involvement and unequalled private sector investment, and government support. Staying one step ahead of opportunities and issues, we mobilize resources to accelerate the economic growth of Greater Halifax.