scholarly journals RDF keyword search using multiple indexes

Filomat ◽  
2018 ◽  
Vol 32 (5) ◽  
pp. 1861-1873 ◽  
Author(s):  
Xiaoqing Lin ◽  
Fu Zhang ◽  
Danling Wang ◽  
Jingwei Cheng
Keyword(s):  
Dynamic Programming ◽  
Keyword Search ◽  
Dynamic Programming Algorithm ◽  
Programming Algorithm ◽  
Path Index ◽  
Shortest Distance ◽  
Data Graph ◽  
Rdf Data ◽  
Entity Relationship ◽  
Entity Relationships

Since SPARQL has been the standard language for querying RDF data, keyword search based on keywords-to-SPARQL translation attracts more intention. However, existing keyword search based on keywords-to-SPARQL translation have limitations that the schema used for keyword-to-SPARQL translation is incomplete so that wrong or incomplete answers are returned and advantages of indexes are not fully taken. To address the issues, an inter-entity relationship summary (ER-summary) is constructed by distilling all the inter-entity relationships of RDF data graph. On ER-summary, we draw circles around each vertex with a given radius r and in the circles we build the shortest property path index (SP-index), the shortest distance index (SD-index) and the r-neighborhoods index by using dynamic programming algorithm. Rather than searching for top-k subgraphs connecting all the keywords centered directly as most existing methods do, we use these indexes to translate keyword queries into SPARQL queries to realize exchanging space for time. Extensive experiments show that our approach is efficient and effective.

RDF Keyword Search by Query Computation

2018 ◽  
Vol 29 (4) ◽  
pp. 1-27 ◽  
Author(s):  
Zongmin Ma ◽  
Xiaoqing Lin ◽  
Li Yan ◽  
Zhen Zhao
Keyword(s):  
Keyword Search ◽  
Priority List ◽  
Graph Expansion ◽  
Path Index ◽  
Degree Of A Vertex ◽  
Rdf Data ◽  
Summary Graph ◽  
Entity Relationship ◽  
Keyword Searches ◽  
Prioritization Scheme

Keyword searches based on the keywords-to-SPARQL translation is attracting more attention because of a growing number of excellent SPARQL search engines. Current approaches for keyword search based on the keywords-to-SPARQL translation suffer from returning incomplete answers or wrong answers due to a lack of underlying schema information. To overcome these difficulties, in this article, we propose a new keyword search paradigm by translating keyword queries into SPARQL queries for exploring RDF data. An inter-entity relationship summary with complete schema information is distilled from the RDF data graph for composing SPARQL queries. To avoid potentially wasteful summary graph expansion, we develop a new search prioritization scheme by combining the degree of a vertex with the distance from the original keyword element. Starting from the ordered priority list that is built in advance, we apply the forward path index to faster find the top-k subgraphs, which are relevant to the conjunction of the entering keywords. The experimental results show that our approach is efficient and scalable.

Optimization in Trajectory Planning of Multi-Jointed Fingers in Dextrous Hand Designs

1991 ◽  
Author(s):  
A. Meghdari ◽  
H. Sayyaadi
Keyword(s):  
Dynamic Programming ◽  
Motion Control ◽  
Trajectory Planning ◽  
Degrees Of Freedom ◽  
Optimization Technique ◽  
Dynamic Programming Algorithm ◽  
Programming Algorithm ◽  
Kinematics And Dynamics ◽  
Feasible Solutions ◽  
Dextrous Hand

Abstract An optimization technique based on the well known Dynamic Programming Algorithm is applied to the motion control trajectories and path planning of multi-jointed fingers in dextrous hand designs. A three fingered hand with each finger containing four degrees of freedom is considered for analysis. After generating the kinematics and dynamics equations of such a hand, optimum values of the joints torques and velocities are computed such that the finger-tips of the hand are moved through their prescribed trajectories with the least time or/and energy to reach the object being grasped. Finally, optimal as well as feasible solutions for the multi-jointed fingers are identified and the results are presented.

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