Graph summarization for source selection of querying over Linked Open Data

2017 ◽  
Author(s):  
Junxian Li ◽  
Wei Wang
Keyword(s):  
Open Data ◽  
Linked Open Data ◽  
Source Selection ◽  
Graph Summarization ◽  
Selection Of

Evidence for a single mechanism gating perceptual and long-term memory information into working memory

2020 ◽  
Author(s):  
Sam Verschooren ◽  
Yoav Kessler ◽  
Tobias Egner
Keyword(s):  
Working Memory ◽  
Long Term Memory ◽  
Sources Of Information ◽  
Term Memory ◽  
Source Selection ◽  
Single Mechanism ◽  
Gating Mechanism ◽  
Opening And Closing ◽  
Selection Of

An influential view of working memory (WM) holds that its’ contents are controlled by a selective gating mechanism that allows for relevant perceptual information to enter WM when opened, but shields WM contents from interference when closed. In support of this idea, prior studies using the reference-back paradigm have established behavioral costs for opening and closing the gate between perception and WM. WM also frequently requires input from long-term memory (LTM), but it is currently unknown whether a similar gate controls the selection of LTM representations into WM, and how WM gating of perceptual vs. LTM sources of information relate to each other. To address these key theoretical questions, we devised a novel version of the reference-back paradigm, where participants switched between gating perceptual and LTM information into WM. We observed clear evidence for gate opening and closing costs in both cases. Moreover, the pattern of costs associated with gating and source-switching indicated that perceptual and LTM information is gated into WM via a single gate, and rely on a shared source-selection mechanism. These findings extend current models of WM gating to encompass LTM information, and outline a new functional WM architecture.

Europeana no Linked Open Data: conceitos de Web Semântica na dimensão aplicada das humanidades digitais

2017 ◽  
Vol 12 (2) ◽  
Author(s):  
Caio Saraiva Coneglian ◽  
José Eduardo Santarem Segundo
Keyword(s):  
Linked Data ◽  
Open Data ◽  
Linked Open Data

O surgimento de novas tecnologias, tem introduzido meios para a divulgação e a disponibilização das informações mais eficientemente. Uma iniciativa, chamada de Europeana, vem promovendo esta adaptação dos objetos informacionais dentro da Web, e mais especificamente no Linked Data. Desta forma, o presente estudo tem como objetivo apresentar uma discussão acerca da relação entre as Humanidades Digitais e o Linked Open Data, na figura da Europeana. Para tal, utilizamos uma metodologia exploratória e que busca explorar as questões relacionadas ao modelo de dados da Europeana, EDM, por meio do SPARQL. Como resultados, compreendemos as características do EDM, pela utilização do SPARQL. Identificamos, ainda, a importância que o conceito de Humanidades Digitais possui dentro do contexto da Europeana.Palavras-chave: Web semântica. Linked open data. Humanidades digitais. Europeana. EDM.Link: https://periodicos.ufsc.br/index.php/eb/article/view/1518-2924.2017v22n48p88/33031

scholarly journals A Hybrid Approach Combining R*-Tree and k-d Trees to Improve Linked Open Data Query Performance

2021 ◽  
Vol 11 (5) ◽  
pp. 2405
Author(s):  
Yuxiang Sun ◽  
Tianyi Zhao ◽  
Seulgi Yoon ◽  
Yongju Lee
Keyword(s):  
Flash Memory ◽  
Query Language ◽  
Hybrid Approach ◽  
Open Data ◽  
Main Memory ◽  
Linked Open Data ◽  
Index Structure ◽  
Identification Algorithm ◽  
Distributed Computing Systems ◽  
Query Performance

Semantic Web has recently gained traction with the use of Linked Open Data (LOD) on the Web. Although numerous state-of-the-art methodologies, standards, and technologies are applicable to the LOD cloud, many issues persist. Because the LOD cloud is based on graph-based resource description framework (RDF) triples and the SPARQL query language, we cannot directly adopt traditional techniques employed for database management systems or distributed computing systems. This paper addresses how the LOD cloud can be efficiently organized, retrieved, and evaluated. We propose a novel hybrid approach that combines the index and live exploration approaches for improved LOD join query performance. Using a two-step index structure combining a disk-based 3D R*-tree with the extended multidimensional histogram and flash memory-based k-d trees, we can efficiently discover interlinked data distributed across multiple resources. Because this method rapidly prunes numerous false hits, the performance of join query processing is remarkably improved. We also propose a hot-cold segment identification algorithm to identify regions of high interest. The proposed method is compared with existing popular methods on real RDF datasets. Results indicate that our method outperforms the existing methods because it can quickly obtain target results by reducing unnecessary data scanning and reduce the amount of main memory required to load filtering results.

Enrichment of EHR with Linked Open Data for Risk Factors Identification

2019 ◽  
Author(s):  
Svetla Boytcheva ◽  
Galia Angelova ◽  
Zhivko Angelov ◽  
Dimitar Tcharaktchiev ◽  
Vlayko Vodenicharov
Keyword(s):  
Risk Factors ◽  
Open Data ◽  
Linked Open Data

scholarly journals The read–write Linked Data Web

2013 ◽  
Vol 371 (1987) ◽  
pp. 20120513 ◽  
Author(s):  
Tim Berners-Lee ◽  
Kieron O’Hara
Keyword(s):  
Future Development ◽  
Linked Data ◽  
Open Data ◽  
Linked Open Data ◽  
The Future ◽  
The Web

This paper discusses issues that will affect the future development of the Web, either increasing its power and utility, or alternatively suppressing its development. It argues for the importance of the continued development of the Linked Data Web, and describes the use of linked open data as an important component of that. Second, the paper defends the Web as a read–write medium, and goes on to consider how the read–write Linked Data Web could be achieved.

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