Study on Digital Content Representation from Direct Label Graph to RDF/OWL Language into Semantic Web

2014 ◽  
Vol 644-650 ◽  
pp. 3304-3309
Author(s):  
Khamis Abdul Latif Khamis ◽  
Luo Zhong ◽  
Hua Zhu Song
Keyword(s):  
Semantic Web ◽  
Expressive Power ◽  
Graph Representation ◽  
Label Graph ◽  
Object Class ◽  
Heritage Sites ◽  
Media Companies ◽  
Rdf Graph ◽  
Media Data ◽  
Direct Label

An increasing number of publication and consumptions of media data on the social and dynamic web has allowed ontology technology to grow up unpredictable. News agencies, cultural heritage sites, social media companies and ordinary users contribute a large portion of media contents across web community. These huge amounts of media contents are generally accessed via standardized and proprietary metadata formats through semantic web. But nearly all cases need specific, standardized, and more expressive methods to represent media data into the knowledge representation paradigm. This paper proposes the proper methods to express media ontology based on the nature of media data. At first RDF graph representation model is used to show the expressive power of domain classification with direct label graph concepts. Secondly, events and object class domain are used to express relational properties of media content. Finally, the events and object class domain is expressed into RDF/OWL language, as preferable and standardized language to represent media data in the semantic web.

Representing n-ary relations in the Semantic Web

2019 ◽  
Author(s):  
Marco Giunti ◽  
Giuseppe Sergioli ◽  
Giuliano Vivanet ◽  
Simone Pinna
Keyword(s):  
Artificial Intelligence ◽  
Semantic Web ◽  
Expressive Power ◽  
Abstract Model ◽  
Relational Ontology ◽  
Rdf Graph ◽  
Labeled Graphs ◽  
Ontology Language ◽  
Technical Simplicity ◽  
In Virtue Of

Abstract Knowledge representation is a central issue for Artificial Intelligence and the Semantic Web. In particular, the problem of representing n-ary relations in RDF-based languages such as RDFS or OWL by no means is an obvious one. With respect to previous attempts, we show why the solutions proposed by the well known W3C Working Group Note on n-ary relations are not satisfactory on several scores. We then present our abstract model for representing n-ary relations as directed labeled graphs, and we show how this model gives rise to a new ontological pattern (parametric pattern) for the representation of such relations in the Semantic Web. To this end, we define PROL (Parametric Relational Ontology Language). PROL is an ontological language designed to express any n-ary fact as a parametric pattern, which turns out to be a special RDF graph. The vocabulary of PROL is defined by a simple RDFS ontology. We argue that the parametric pattern may be particularly beneficial in the context of the Semantic Web, in virtue of its high expressive power, technical simplicity, and faithful meaning rendition. Examples are also provided.

scholarly journals Building an OWL ontology with Xper3

2018 ◽  
Vol 2 ◽  
pp. e25614 ◽  
Author(s):  
Florian Pellen ◽  
Sylvain Bouquin ◽  
Isabelle Mougenot ◽  
Régine Vignes-Lebbe
Keyword(s):  
Semantic Web ◽  
Knowledge Base ◽  
Expressive Power ◽  
Knowledge Bases ◽  
User Friendliness ◽  
Standard Format ◽  
Ontology Language ◽  
Closed World ◽  
Web Standards ◽  
Description Framework

Xper3 (Vignes Lebbe et al. 2016) is a collaborative knowledge base publishing platform that, since its launch in november 2013, has been adopted by over 2 thousand users (Pinel et al. 2017). This is mainly due to its user friendly interface and the simplicity of its data model. The data are stored in MySQL Relational DBs, but the exchange format uses the TDWG standard format SDD (Structured Descriptive DataHagedorn et al. 2005). However, each Xper3 knowledge base is a closed world that the author(s) may or may not share with the scientific community or the public via publishing content and/or identification key (Kopfstein 2016). The explicit taxonomic, geographic and phenotypic limits of a knowledge base are not always well defined in the metadata fields. Conversely terminology vocabularies, such as Phenotype and Trait Ontology PATO and the Plant Ontology PO, and software to edit them, such as Protégé and Phenoscape, are essential in the semantic web, but difficult to handle for biologist without computer skills. These ontologies constitute open worlds, and are expressed themselves by RDF triples (Resource Description Framework). Protégé offers vizualisation and reasoning capabilities for these ontologies (Gennari et al. 2003, Musen 2015). Our challenge is to combine the user friendliness of Xper3 with the expressive power of OWL (Web Ontology Language), the W3C standard for building ontologies. We therefore focused on analyzing the representation of the same taxonomic contents under Xper3 and under different models in OWL. After this critical analysis, we chose a description model that allows automatic export of SDD to OWL and can be easily enriched. We will present the results obtained and their validation on two knowledge bases, one on parasitic crustaceans (Sacculina) and the second on current ferns and fossils (Corvez and Grand 2014). The evolution of the Xper3 platform and the perspectives offered by this link with semantic web standards will be discussed.

Probabilistic Models for the Semantic Web

2010 ◽  
pp. 74-105 ◽  
Author(s):  
Livia Predoiu
Keyword(s):  
Semantic Web ◽  
Knowledge Representation ◽  
Classical Logic ◽  
Probabilistic Models ◽  
Expressive Power ◽  
Knowledge Representation And Reasoning ◽  
Uncertain Information ◽  
New Approaches ◽  
The Web

Recently, there has been an increasing interest in formalisms for representing uncertain information on the Semantic Web. This interest is triggered by the observation that knowledge on the web is not always crisp and we have to be able to deal with incomplete, inconsistent and vague information. The treatment of this kind of information requires new approaches for knowledge representation and reasoning on the web as existing Semantic Web languages are based on classical logic which is known to be inadequate for representing uncertainty in many cases. While different general approaches for extending Semantic Web languages with the ability to represent uncertainty are explored, we focus our attention on probabilistic approaches. We survey existing proposals for extending semantic web languages or formalisms underlying Semantic Web languages in terms of their expressive power, reasoning capabilities as well as their suitability for supporting typical tasks associated with the Semantic Web.

A Review of Fuzzy Models for the Semantic Web

2011 ◽  
pp. 63-77
Author(s):  
Hailong Wang ◽  
Zongmin Ma ◽  
Li Yan ◽  
Jingwei Cheng
Keyword(s):  
Computational Complexity ◽  
Semantic Web ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Description Logics ◽  
Expressive Power ◽  
Semantic Knowledge ◽  
Context Information ◽  
Semantic Knowledge Base

In the Semantic Web context, information would be retrieved, processed, shared, reused and aligned in the maximum automatic way possible. Our experience with such applications in the Semantic Web has shown that these are rarely a matter of true or false but rather procedures that require degrees of relatedness, similarity, or ranking. Apart from the wealth of applications that are inherently imprecise, information itself is many times imprecise or vague. In order to be able to represent and reason with such type of information in the Semantic Web, different general approaches for extending semantic web languages with the ability to represent imprecision and uncertainty has been explored. In this chapter, we focus our attention on fuzzy extension approaches which are based on fuzzy set theory. We review the existing proposals for extending the theoretical counterpart of the semantic web languages, description logics (DLs), and the languages themselves. The following statements will include the expressive power of the fuzzy DLs formalism and its syntax and semantic, knowledge base, the decidability of the tableaux algorithm and its computational complexity etc. Also the fuzzy extension to OWL is discussed in this chapter.

scholarly journals WINFRA: A Web-Based Platform for Semantic Data Retrieval and Data Analytics

Mathematics ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 2090
Author(s):  
Addi Ait-Mlouk ◽  
Xuan-Son Vu ◽  
Lili Jiang
Keyword(s):  
Semantic Web ◽  
Association Rules ◽  
Language Processing ◽  
Data Analytics ◽  
Data Retrieval ◽  
Heterogeneous Data ◽  
Graph Representation ◽  
Knowledge Graph ◽  
Multiple Sources ◽  
Semantic Data

Given the huge amount of heterogeneous data stored in different locations, it needs to be federated and semantically interconnected for further use. This paper introduces WINFRA, a comprehensive open-access platform for semantic web data and advanced analytics based on natural language processing (NLP) and data mining techniques (e.g., association rules, clustering, classification based on associations). The system is designed to facilitate federated data analysis, knowledge discovery, information retrieval, and new techniques to deal with semantic web and knowledge graph representation. The processing step integrates data from multiple sources virtually by creating virtual databases. Afterwards, the developed RDF Generator is built to generate RDF files for different data sources, together with SPARQL queries, to support semantic data search and knowledge graph representation. Furthermore, some application cases are provided to demonstrate how it facilitates advanced data analytics over semantic data and showcase our proposed approach toward semantic association rules.

scholarly journals Interactive 3D Exploration of RDF Graphs through Semantic Planes

2018 ◽  
Vol 10 (8) ◽  
pp. 81 ◽  
Author(s):  
Fabio Viola ◽  
Luca Roffia ◽  
Francesco Antoniazzi ◽  
Alfredo D’Elia ◽  
Cristiano Aguzzi ◽  
...  
Keyword(s):  
Semantic Web ◽  
3D Visualization ◽  
Data Representation ◽  
Knowledge Bases ◽  
Rdf Graph ◽  
Common Concept ◽  
Interactive 3D ◽  
3D Scene ◽  
Rdf Graphs ◽  
3D Exploration

This article presents Tarsier, a tool for the interactive 3D visualization of RDF graphs. Tarsier is mainly intended to support teachers introducing students to Semantic Web data representation formalisms and developers in the debugging of applications based on Semantic Web knowledge bases. The tool proposes the metaphor of semantic planes as a way to visualize an RDF graph. A semantic plane contains all the RDF terms sharing a common concept; it can be created, and further split into several planes, through a set of UI controls or through SPARQL 1.1 queries, with the full support of OWL and RDFS. Thanks to the 3D visualization, links between semantic planes can be highlighted and the user can navigate within the 3D scene to find the better perspective to analyze data. Data can be gathered from generic SPARQL 1.1 protocol services. We believe that Tarsier will enhance the human friendliness of semantic technologies by: (1) helping newcomers assimilate new data representation formats; and (2) increasing the capabilities of inspection to detect relevant situations even in complex RDF graphs.

An Efficient Approach for Ranking of Semantic Web Documents by Computing Semantic Similarity and Using HCS Clustering

2021 ◽  
Vol 5 (1) ◽  
pp. 45-56
Author(s):  
Poonam Chahal ◽  
Manjeet Singh
Keyword(s):  
Semantic Web ◽  
Semantic Similarity ◽  
Semantic Analysis ◽  
Semantic Content ◽  
Graph Representation ◽  
Graphical Form ◽  
Theoretic Approach ◽  
Connected Subgraph ◽  
Web Documents ◽  
The Web

In today's era, with the availability of a huge amount of dynamic information available in world wide web (WWW), it is complex for the user to retrieve or search the relevant information. One of the techniques used in information retrieval is clustering, and then the ranking of the web documents is done to provide user the information as per their query. In this paper, semantic similarity score of Semantic Web documents is computed by using the semantic-based similarity feature combining the latent semantic analysis (LSA) and latent relational analysis (LRA). The LSA and LRA help to determine the relevant concepts and relationships between the concepts which further correspond to the words and relationships between these words. The extracted interrelated concepts are represented by the graph further representing the semantic content of the web document. From this graph representation for each document, the HCS algorithm of clustering is used to extract the most connected subgraph for constructing the different number of clusters which is according to the information-theoretic approach. The web documents present in clusters in graphical form are ranked by using the text-rank method in combination with the proposed method. The experimental analysis is done by using the benchmark datasets OpinRank. The performance of the approach on ranking of web documents using semantic-based clustering has shown promising results.

A Modal Defeasible Reasoner of Deontic Logic for the Semantic Web

2011 ◽  
Vol 7 (1) ◽  
pp. 18-43 ◽  
Author(s):  
Efstratios Kontopoulos ◽  
Nick Bassiliades ◽  
Guido Governatori ◽  
Grigoris Antoniou
Keyword(s):  
Modal Logic ◽  
Semantic Web ◽  
Deontic Logic ◽  
Expressive Power ◽  
Modal Logics ◽  
Cognitive State ◽  
Privacy Requirements ◽  
Defeasible Logic ◽  
Conflicting Information ◽  
Web Information

Defeasible logic is a non-monotonic formalism that deals with incomplete and conflicting information, whereas modal logic deals with the concepts of necessity and possibility. These types of logics play a significant role in the emerging Semantic Web, which enriches the available Web information with meaning, leading to better cooperation between end-users and applications. Defeasible and modal logics, in general, and, particularly, deontic logic provide means for modeling agent communities, where each agent is characterized by its cognitive profile and normative system, as well as policies, which define privacy requirements, access permissions, and individual rights. Toward this direction, this article discusses the extension of DR-DEVICE, a Semantic Web-aware defeasible reasoner, with a mechanism for expressing modal logic operators, while testing the implementation via deontic logic operators, concerned with obligations, permissions, and related concepts. The motivation behind this work is to develop a practical defeasible reasoner for the Semantic Web that takes advantage of the expressive power offered by modal logics, accompanied by the flexibility to define diverse agent behaviours. A further incentive is to study the various motivational notions of deontic logic and discuss the cognitive state of agents, as well as the interactions among them.

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