BNOSA: A Bayesian network and ontology based semantic annotation framework

Rajput, Quratulain; Haider, Sajjad

doi:10.1016/j.websem.2011.04.002

Cited by 15 publications

(13 citation statements)

References 21 publications

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“…The semantic interface proposed for external systems containing the HTML and an RDF with the semantic annotations of each article offers a well defined structure that reuses Semantic Web resources and that can be perfectly consumed by any external agent. The reliability of semiautomatically-produced semantic annotations is guaranteed by the fact that in addition to the automatic generation of annotations, the person who is annotating the text can manually remove or add annotations according to his/her understanding of the text [5,10] . The annotation of concepts that were not directly quoted in the text but are present due to their relation to some annotated concept is also made.…”

Section: Discussionmentioning

confidence: 99%

Towards a semantic-based content management system for journalistic writing

Deus

Ishikawa

Oliveira

et al. 2018

Proceedings of the 10th International Conference on Management of Digital EcoSystems

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Semantics is still a challenge to automation and to the improvement of the relationship between humans and machines. Content management systems have a lot of improvement possibilities using semantics. A news writing process incorporating a content management system that provides semantic search, semantic relationships between articles and communication with external semantic systems can improve the productivity of the writers and make the reader's task easier. This work presents a functional prototype of a content management system which focuses on the construction of semantic annotations based on domain ontology, reuse annotations in search and on relationship construction between stored texts, providing a semantic interface for external systems. We present in this paper the annotation algorithm, the use cases of annotation, article creation and editing, as well as an approach for doing a semantic search and creating semantic relationships between texts. The system enables users to create semantic annotations quickly and allows them to remove and add annotations, including those suggested by the annotation algorithm. The two approaches for semantic relationships between texts are accurate and useful, while the search tool is versatile because it allows users to search in semantic and non semantic fields at the same time and it also uses logic operators in all fields.

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Section: Discussionmentioning

confidence: 99%

Towards a semantic-based content management system for journalistic writing

Deus

Ishikawa

Oliveira

et al. 2018

Proceedings of the 10th International Conference on Management of Digital EcoSystems

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“…Given the advantages provided, ontologies have been incorporated in a variety of applications in different application fields [1], [17], [18].…”

Section: Semantic Web Linked Data and The Use Of Ontologiesmentioning

confidence: 99%

“…In addition, through the petition mechanism, the petitions organized in each country may promote issues of interest to be discussed by the appropriate organization or institution, such as the country's Parliament. There are also initiatives that offer the code of the petition software freely to the community, such as the Drupal installation profile powering "We The People" for the USA Whitehouse 16 and the code base for the UK Government's e-petitions service 17 . In this way the users will have the opportunity to organize public petitions with regards to requesting open data from both public and private institutions.…”

Section: Demand For Datasetsmentioning

confidence: 99%

A Semantic Web Approach in the Implementation of a Linked Data Portal Using a CMS

Giannopoulou

Mitrou

Chimos

et al. 2014

2014 Tenth International Conference on Signal-Image Technology and Internet-Based Systems

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In this work, a semantic web framework is proposed. The aim of the framework is to semantically process and link data from different sources. The proposed framework embeds multiple entry channels for different target groups and motivations to re-use, report, comment and share content. The implementation is built on top of a Content Management System. In this approach we are using Drupal but any other CMS can be used alternatively. Even though in our paradigm the sources are mainly from an institution's data, namely National Technical University of Athens (NTUA) digital library, the utilization of the proposed architecture can be directly extended to additional fields.

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“…The semantic concepts can be expressed by ontology, which has the following advantages. Firstly, the ontology can be reused [12] to eliminate the repetitive calculations of raw data. Secondly, the ontology and their relationships can be defined at different levels in the semantic network, which is good for the semantic richness of data and semantic reasoning of behavior.…”

Section: Introductionmentioning

confidence: 99%

Semantic Modelling of Ship Behavior in Harbor Based on Ontology and Dynamic Bayesian Network

Wen

Zhang

Huang

et al. 2019

IJGI

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Recognizing ship behavior is important for maritime situation awareness and intelligent transportation management. Some scholars extracted ship behaviors from massive trajectory data by statistical analysis. However, the meaning of the behaviors, i.e., semantic meanings of behaviors and their relationships, are not explicit. Ship behaviors are affected by navigational area and traffic rules, so their meanings can be obtained only in specific maritime situations. The work establishes the semantic model of ship behavior (SMSB) to represent and reason the meaning of the behaviors. Firstly, a semantic network is built based on maritime traffic rules and good seamanship. The corresponding detection methods are then proposed to identify basic ship behaviors in various maritime scenes, including dock, anchorage, traffic lane, and general scenes. After that, dynamic Bayesian network (DBN) is used to reason potential ship behaviors. Finally, trajectory annotation and semantic query of the model are validated in the different scenes of harbor. The basic behaviors and potential behaviors in all typical scenes of any harbor can be obtained accurately and expressed conveniently using the proposed model. The model facilitates the ships behavior research, contributing to the semantic trajectory analysis.

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BNOSA: A Bayesian network and ontology based semantic annotation framework

Cited by 15 publications

References 21 publications

Towards a semantic-based content management system for journalistic writing

Towards a semantic-based content management system for journalistic writing

A Semantic Web Approach in the Implementation of a Linked Data Portal Using a CMS

Semantic Modelling of Ship Behavior in Harbor Based on Ontology and Dynamic Bayesian Network

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