Usage of the Jess Engine, Rules and Ontology to Query a Relational Database

Bak, Jaroslaw; Jędrzejek, Czesław; Falkowski, Maciej

doi:10.1007/978-3-642-04985-9_21

Cited by 11 publications

(3 citation statements)

References 6 publications

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“…Results are ordered in ascending order by the ?date-Created property to get a chronological list of minefield records. This query may be executed in the Protégé ontology editor [56,57] extended with the Jess rule engine [58]. The forward chaining search strategy should be used to maximize the number of returned tuples and multimedia documents [59].…”

Section: Minefield Observatory Structurementioning

confidence: 99%

Ontology-Based Data Observatory for Formal Knowledge Representation of UXO Using Advanced Semantic Web Technologies

Horvat,

Krtalić,

Akagić

et al. 2024

Electronics

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As landmines and other unexploded ordnances (UXOs) present a great risk to civilians and infrastructure, humanitarian demining is an essential component of any post-conflict reconstruction. This paper introduces the Minefield Observatory, a novel web-based datastore service that semantically integrates diverse data in humanitarian demining to comprehensively and formally describe suspected minefields. Because of the high heterogeneity and isolation of the available minefield datasets, extracting relevant information to determine the optimal course of demining efforts is time-consuming, labor-intensive and requires highly specialized knowledge. Data consolidation and artificial intelligence techniques are used to convert unstructured data sources and store them in an ontology-based knowledge database that can be efficiently accessed through a Semantic Web application serving as the Minefield Observatory user interface. The MINEONT+ ontology was developed to integrate diverse mine scene information obtained through non-technical surveys and remote sensing, such as aerial and hyperspectral satellite imagery, indicators of mine presence and absence, contextual data, terrain analysis information, and battlefield reports. The Minefield Observatory uses the Microdata API to embed this dataset into dynamic HTML5 content, allowing seamless usage in a user-centric web tool. A use-case example was provided demonstrating the viability of the proposed approach.

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Section: Minefield Observatory Structurementioning

confidence: 99%

Ontology-Based Data Observatory for Formal Knowledge Representation of UXO Using Advanced Semantic Web Technologies

Horvat,

Krtalić,

Akagić

et al. 2024

Electronics

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“…The architecture for ontology based reasoning typically involves the use of a rule based expert system (e.g., Java Expert System Shell), a reasoner (e.g., RacerPro or Pellet), and a knowledge base. Design science researchers and knowledge engineers commonly employ this architecture in application areas such as finance, eCommerce, and medicine (Bak, Jedrzejek, & Falkowski, 2009;Bouamrane, Rector, & Hurrell, 2009;O'Connor, Shankar, Nyulas, Tu, & Das, 2008). Their utility for knowledge representation (Bera, Burton-Jones, & Wand, 2011;Y.-J.…”

Section: Implementation Architecturementioning

confidence: 99%

Designing a Semantic Tool to Evaluate Web Content of Government Websites

Thomas

Alalwan²

2016

International Journal of Public Administration in the Digital Age

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E-government initiatives provide enormous volume of information via online content. As public information changes over time due to changes in laws and regulations, maintaining the currency and consistency of the web content becomes acutely important. Government agencies have to regularly evaluate the web content (WC) to ensure high quality of information available to the citizens, businesses and public administrators. Currently there exists no standardized approach for monitoring and maintaining WC. By analyzing the guidelines of three government organizations, the authors develop WC ontology for the systematic and formal representation of the concepts and functions in evaluating web content. An ontology-based evaluation tool is proposed that can be used to improve the quality of web content and efficiency of the evaluation process. The ontological approach holds promising features and benefits including information sharing, reducing time and paper work during evaluation, assuring more accurate results, and communicating evaluation results to knowledge engineers, public administrators, evaluators and decision makers associated with e-government initiatives.

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“…The main work of this paper is divided into two aspects: Firstly, the definition and formalized model of malware intention are given and the rationality of this model is proved. Secondly, we use ontology to model the semantic relationship between behaviors and objects and automate the process of intention derivation using SWRL [8] rules and Jess engine [9]. SWRL is a semantic web rule language combining OWL and RuleML and also a language that presents rules in a semantic way.…”

Section: Introductionmentioning

confidence: 99%

Behavior Intention Derivation of Android Malware Using Ontology Inference

Jiao

Liu

Chen

et al. 2018

Journal of Electrical and Computer Engineering

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Previous researches on Android malware mainly focus on malware detection, and malware’s evolution makes the process face certain hysteresis. The information presented by these detected results (malice judgment, family classification, and behavior characterization) is limited for analysts. Therefore, a method is needed to restore the intention of malware, which reflects the relation between multiple behaviors of complex malware and its ultimate purpose. This paper proposes a novel description and derivation model of Android malware intention based on the theory of intention and malware reverse engineering. This approach creates ontology for malware intention to model the semantic relation between behaviors and its objects and automates the process of intention derivation by using SWRL rules transformed from intention model and Jess inference engine. Experiments on 75 typical samples show that the inference system can perform derivation of malware intention effectively, and 89.3% of the inference results are consistent with artificial analysis, which proves the feasibility and effectiveness of our theory and inference system.

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Usage of the Jess Engine, Rules and Ontology to Query a Relational Database

Cited by 11 publications

References 6 publications

Ontology-Based Data Observatory for Formal Knowledge Representation of UXO Using Advanced Semantic Web Technologies

Ontology-Based Data Observatory for Formal Knowledge Representation of UXO Using Advanced Semantic Web Technologies

Designing a Semantic Tool to Evaluate Web Content of Government Websites

Behavior Intention Derivation of Android Malware Using Ontology Inference

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