scholarly journals SSONDE: Semantic Similarity on LiNked Data Entities

2012 ◽  
pp. 25-36
Author(s):  
Riccardo Albertoni ◽  
Monica De Martino
Keyword(s):  
Semantic Similarity ◽  
Linked Data

Intelligent navigation of linked data with a graphical interface based on semantic similarity

2019 ◽  
Author(s):  
Pedro Fonseca-Ortiz ◽  
Hector G. Ceballos
Keyword(s):  
User Interface ◽  
Semantic Web ◽  
Semantic Similarity ◽  
Linked Data ◽  
Recommendation System ◽  
Web Applications ◽  
Graphical Interface ◽  
User Interest ◽  
Specialized Knowledge ◽  
Semantic Web Technology

"Semantic Web Technology proposes the use of linked data and ontologies as a mean for providing meaning to information. Even though several tools for the analysis and visualization of linked data exist, these tools require a lot of specialized knowledge to fulfill a purpose. Additionally, this complexity hardens its use for nonexperienced users therefore limiting semantic web applications. This paper describes a tool that combines the use of a recommendation system and an intuitive dynamic user interface for navigating linked data. The tool guides the user to find resources of interest by highlighting those related to his search intention. This is, the platform learns on the fly the user interest and makes recommendations based on the connections between resources."

scholarly journals Linked Forests: Semantic similarity of geographical concepts “forest”

2016 ◽  
Vol 8 (1) ◽  
Author(s):  
Otakar Čerba ◽  
Karel Jedlička
Keyword(s):  
Object Relations ◽  
Semantic Similarity ◽  
Linked Data ◽  
Geographical Data ◽  
Semantic Relationships ◽  
Tanimoto Coefficient ◽  
Explicit Information ◽  
Tversky Index

AbstractLinked Data represents the new trend in geoinformatics and geomatics. It produces a structure of objects (in a form of concepts or terms) interconnected by object relations expressing a type of semantic relationships of various concepts. The research published in this article studies, if objects connected by above mentioned relations are more similar than objects representing the same phenomenon, but standing alone. The phenomenon “forest” and relevant geographical concepts were chosen as the domain of the research. The concepts similarity (Tanimoto coefficient as a specification of Tversky index) was computed on the basis of explicit information provided by thesauri containing particular concepts. Overall in the seven thesauri (AGROVOC, EuroVoc, GEMET, LusTRE/EARTh, NAL, OECD and STW) there was tested if the “forest” concept interconnected by the relation skos:exactMatch are more similar than other, not interlinked concepts. The results of the research are important for the sharing and combining of geographical data, information and knowledge. The proposed methodology can be reused to a comparison of other geographical concepts.

Research on Parallel Computation of Semantic Similarity in Linked Data

2014 ◽  
Vol 1049-1050 ◽  
pp. 1320-1326
Author(s):  
Xiao Jin ◽  
Xing Jin Zhang ◽  
Zhi Yun Zheng ◽  
Quan Min Li ◽  
Li Ping Lu
Keyword(s):  
Parallel Computing ◽  
Parallel Computation ◽  
Semantic Similarity ◽  
Linked Data ◽  
Computing Methods ◽  
Programming Techniques ◽  
Speed Up ◽  
Low Efficiency ◽  
Hadoop Cluster ◽  
Computing Method

This paper proposes a novel parallel computing method of semantic similarity in linked data to solve such problems as low efficiency and data dispersion.It combines the existing similarity calculation method with MapReduce parallel computation framework to design the appropriate parallel computing method of similarity. First, three typical similarity computing methods and the parallel programming models are introduced. Then according to the MapReduce programming techniques of cloud computing, the parallel computation of similarity in linked data is proposed. The experimental results show that, compared with the traditional platforms, the parallel computing method of similarity on the Hadoop cluster not only improves the capacity and efficiency in the processing massive data, but also has a better speed-up ratio and augmentability.

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