Conflict resolution and missing completion in the fusion of domain ontology in cyber-physical systems

CPS integrates information services, human resource services, and physical equipment services, and always be supported by the ontologies in multiple domains. Due to the inconsistency of ontologies from different domains, the fusion of domain ontologies may have conflicts and deficiencies. Therefore, this paper provides a method for the conflict resolution and missing completion in the fusion of domain.

Expert System of Anti-Diabetic Medicine Selection

The Prediction of World Health Organization (WHO) estimates that in 2030 the number of diabetics in Indonesia reached approximately 21.3 million people. Moreover, the development of medicine consumed by diabetics also varies. In this paper, we present a system that represents a diabetes expert into a knowledge based on the domain ontology. The early stage of the system is developing drugs ontology (including functions and contraindications) and patient ontology. Then, matching a weighted ontology will give drugs recommendations that are suitable with the patient's condition. The system is able to analyze diabetes symptoms to give drugs recommendations to the patient.

Improving Readability of Online Privacy Policies through DOOP: A Domain Ontology for Online Privacy

Privacy policies play an important part in informing users about their privacy concerns by operating as memorandums of understanding (MOUs) between them and online services providers. Research suggests that these policies are infrequently read because they are often lengthy, written in jargon, and incomplete, making them difficult for most users to understand. Users are more likely to read short excerpts of privacy policies if they pertain directly to their concern. In this paper, a novel approach and a proof-of-concept tool are proposed that reduces the amount of privacy policy text a user has to read. It does so using a domain ontology and natural language processing (NLP) to identify key areas of the policies that users should read to address their concerns and take appropriate action. Using the ontology to locate key parts of privacy policies, average reading times were substantially reduced from 29 to 32 min to 45 s.

METHOD OF DOMAIN ONTOLOGY AUTOMATED REPLENISHMENT FOR THE SUPPORT OF NEW TECHNICAL SOLUTIONS SYNTHESIS. PART I

To solve the problem of information support for the synthesis of new technical solutions, a method of extracting structured data from an array of Russian-language patents is presented. The key features of the invention, such as the structural elements of the technical object and the relationships between them, are considered as information support. The data source addresses the main claim of the invention in the device patent. The unit of extraction is the semantic structure Subject-Action-Object (SAO), which semantically describes the constructive elements. The extraction method is based on shallow parsing and claim segmentation, taking into account the specifics of writing patent texts. Often the excessive length of the claim sentence and the specificity of the patent language make it difficult to efficiently use off-the-shelf tools for data extracting. All processing steps include: segmentation of the claim sentences; extraction of primary SAO structures; construction of the graph of the construct elements f the invention; integration of the data into the domain ontology. This article deals with the first two stages. Segmentation is carried out according to a number of heuristic rules, and several natural language processing tools are used to reduce analysis errors. The primary SAO elements are extracted considering the valences of the predefined semantic group of verbs, as well as information about the type of processed segment. The result of the work is the organization of the domain ontology, which can be used to find alternative designs for nodes in a technical object. In the second part of the article, an algorithm for constructing a graph of structural elements of a separate technical object, an assessment of the effectiveness of the system, as well as ontology organization and the result are considered.

Construction and applications of knowledge graph of porphyry copper deposits

A knowledge graph is becoming popular due to its ability to describe the real world by using a graph language that can be understood by both humans and machines using computer technologies. A case study to construct the knowledge graph of porphyry copper deposits is presented in this paper. First of all, the raw text data is collected and integrated from selected porphyry copper deposits and porphyry-skarn copper deposits in the Qinzhou Bay – Hangzhou Bay metallogenic belt, South China. Second, the text's entities, relations, and attributes are labeled and extracted with reference to the conceptual model of porphyry copper deposits in the study area. The third, a knowledge graph of porphyry copper deposits, was constructed using Neo4j 4.3. The resulted knowledge graph of porphyry copper deposit has the basic functions of an application. Furthermore, as part of a planned integrated knowledge graph from a single deposit, through an upper-geared metallogenic series, to a high-top metallogenic province, the understanding from the present study may be extended to mineral resource prospectivity and assessment beyond today. The interrelationship between the earth system, the metallogenic system, the exploration system, and the prospectivity and assessment (ES-MS-ES-PS) should be completely understood, and a knowledge graph system for ES-MS-ES-PS is needed. The key scientific and technological problems for achieving the ES-MS-ES-PS knowledge graph system are included in the progressively relative system of the domain ontology and knowledge graph of ES-MS-ES-PS, the automatic construction technology of complicated ESMS-ES-PS domain ontology and knowledge graph, the self-evolution and complementary techniques for multi-modal correlation data embedding in the ES-MS-ES-PS knowledge graph, and the knowledge graph, big data mining and artificial intelligence based on ES-resource prospectivity, and assessment theory, and methods.

TOWARDS THE AUTOMATIC ONTOLOGY GENERATION AND ALIGNMENT OF BIM AND GIS DATA FORMATS

Establishing semantic interoperability between BIM and GIS is vital for geospatial information exchange. Semantic web have a natural ability to provide seamless semantic representation and integration among the heterogeneous domains like BIM and GIS through employing ontology. Ontology models can be defined (or generated) using domain-data representations and further aligned across other ontologies by the semantic similarity of their entities - introducing cross-domain ontologies to achieve interoperability of heterogeneous information. However, due to extensive semantic features and complex alignment (mapping) relations between BIM and GIS data formats, many approaches are far from generating semantically-rich ontologies and perform effective alignment to address geospatial interoperability. This study highlights the fundamental perspectives to be addressed for BIM and GIS interoperability and proposes a comprehensive conceptual framework for automatic ontology generation followed by ontology alignment of open-standards for BIM and GIS data formats. It presents an approach based on transformation patterns to automatically generate ontology models, and semantic-based and structure-based alignment techniques to form cross-domain ontology. Proposed two-phase framework provides ontology model generation for input XML schemas (i.e. of IFC and CityGML formats), and illustrates alignment technique to potentially develop a cross-domain ontology. The study concludes anticipated results of cross-domain ontology can provides future perspectives in knowledge-discovery applications and seamless information exchange for BIM and GIS.

Development of ontology-based model to support learning process in LMS

<p>E-Learning is an important support mechanism for educational systems to increase the efficiency of the education process including students and teachers. The current e-learning systems typically lack the level of metacognitive awareness, adaptive tutoring, and time management skills and have not always met the expectations of the learners as required. In this study, we introduce a novel ontological model for the learning process in the e-learning domain. In the framework, we have built a domain ontology that represents knowledge of the learning, the outcome domain ontology covers the whole learning process. We focused on the learning process ontology model conceptualizing knowledge constructions, such as learning courses, and we present the created course and learning process ontology in detail. In this work, we considered three layers of learning process. The top layer defines a general framework of learning process, conceptual model layer, defines the framework of the actual process of the learning process and course ontology model contains the knowledge unit of the learning process. The prototype ontology is constructed in protégé and managed by Java web ontology language-application programming interface (OWL-API). As a result, our model can solve the problems of current e-tutor systems. Also, it can be used for different domain in e-tutor systems. It can reach the characteristics of standardization, reusability, flexibility, and open knowledge. By applying this model, we can avoid applying isolated databases. The constructed ontology can be used in the future to control adaptive intelligent e-tutor frameworks.</p>