scholarly journals Construction and application research of knowledge graph in aviation risk field

2018 ◽  
Vol 151 ◽  
pp. 05003 ◽  
Author(s):  
Qian Zhao ◽  
Qing Li ◽  
Jingqian Wen
Keyword(s):  
Information Organization ◽  
Knowledge Graph ◽  
Knowledge Mapping ◽  
Construction Technology ◽  
Aviation Accidents ◽  
Risk Event ◽  
Description Framework ◽  
Aviation Safety Reporting System ◽  
Incremental Construction ◽  
Aviation Risk

Since the causes of aviation accidents and risks are complicated, concealed, unpredictable and difficult to be investigated, in order to achieve the efficient organization and knowledge sharing of the historical cases of aviation risk events, this paper put forward the method of constructing vertical knowledge graph for aviation risk field. Firstly, the data-driven incremental construction technology is used to build aviation risk event ontology model. Secondly, the pattern-based knowledge mapping mechanism, which transform structured data into RDF (Resource Description Framework) data for storage, is proposed. And then the application, update and maintenance of the knowledge graph are described. Finally, knowledge graph construction system in aviation risk field is developed; and the data from American Aviation Safety Reporting System (ASRS) is used as an example to verify the rationality and validity of the knowledge graph construction method. Practice has proved that the construction of knowledge graph has a guiding significance for the case information organization and sharing on the field of aviation risk.

scholarly journals Automated construction technology of the government agencies knowledge graph based on the topical crawler

2020 ◽  
Vol 1656 ◽  
pp. 012016
Author(s):  
Ziqi Xiong ◽  
Dezhi Kong ◽  
Zhichao Xia ◽  
Yankai Xue ◽  
Ziyu Song ◽  
...  
Keyword(s):  
Knowledge Graph ◽  
Government Agencies ◽  
Construction Technology ◽  
The Government

Building the Knowledge Graph for Zakat (KGZ) in Indonesian Language

2021 ◽  
Vol 16 ◽  
pp. 1-10
Author(s):  
Husni Teja Sukmana ◽  
JM Muslimin ◽  
Asep Fajar Firmansyah ◽  
Lee Kyung Oh
Keyword(s):  
Named Entity Recognition ◽  
General Purpose ◽  
Entity Recognition ◽  
Basic Knowledge ◽  
Knowledge Graph ◽  
Specific Domain ◽  
Named Entity ◽  
Description Framework ◽  
General Source ◽  
Domain Information

In Indonesia, philanthropy is identical to Zakat. Zakat belongs to a specific domain because it has its characteristics of knowledge. This research studied knowledge graph in the Zakat domain called KGZ which is conducted in Indonesia. This area is still rarely performed, thus it becomes the first knowledge graph for Zakat in Indonesia. It is designed to provide basic knowledge on Zakat and managing the Zakat in Indonesia. There are some issues with building KGZ, firstly, the existing Indonesian named entity recognition (NER) is non-restricted and general-purpose based which data is obtained from a general source like news. Second, there is no dataset for NER in the Zakat domain. We define four steps to build KGZ, involving data acquisition, extracting entities and their relationship, mapping to ontology, and deploying knowledge graphs and visualizations. This research contributed a knowledge graph for Zakat (KGZ) and a building NER model for Zakat, called KGZ-NER. We defined 17 new named entity classes related to Zakat with 272 entities, 169 relationships and provided labelled datasets for KGZ-NER that are publicly accessible. We applied the Indonesian-Open Domain Information Extractor framework to process identifying entities’ relationships. Then designed modeling of information using resources description framework (RDF) to build the knowledge base for KGZ and store it to GraphDB, a product from Ontotext. This NER model has a precision 0.7641, recall 0.4544, and F1-score 0.5655. The increasing data size of KGZ is required to discover all of the knowledge of Zakat and managing Zakat in Indonesia. Moreover, sufficient resources are required in future works.

scholarly journals COMPREHENSIVE RISK MANAGEMENT USING FUZZY FMEA AND MCDA TECHNIQUES IN HIGHWAY CONSTRUCTION PROJECTS

2016 ◽  
Vol 23 (2) ◽  
pp. 300-310 ◽  
Author(s):  
Mohsen AHMADI ◽  
Kourosh BEHZADIAN ◽  
Abdollah ARDESHIR ◽  
Zoran KAPELAN
Keyword(s):  
Construction Projects ◽  
Fuzzy Ahp ◽  
Highway Construction ◽  
Response Strategy ◽  
Construction Technology ◽  
Risk Response ◽  
Best Response ◽  
Fuzzy Fmea ◽  
Target Values ◽  
Risk Event

This paper presents a comprehensive framework to manage the main risk events of highway construction pro­jects within three stages: (1) identification of potential risks; (2) assessment and prioritisation of identified risks based on fuzzy FMEA; (3) identification of appropriate response. The main criteria analysed for prioritising potential risk events are cost, time and quality which are quantified and combined using fuzzy AHP. A new expert system is suggested for identifying an appropriate risk response strategy for a risk event based on risk factor, control number and risk alloca­tion. The best response action for a risk event is then identified with respect to the same criteria using “scope expected deviation” (SED) index. The proposed methodology is demonstrated for management of risk events in a construction project of Bijar-Zanjan highway in Iran. For the risk event of “increase in tar price”, deviation from the target values of the criteria is analysed for business-as-usual state plus two risk response actions using SED index. The results show that the response action of “changing paving construction technology from asphalt pavement to RCC pavement” can success­fully cope with the risk event of “increase in tar price” and have the minimum deviation.

scholarly journals Construction and applications of knowledge graph of porphyry copper deposits

2021 ◽  
Vol 44 (3) ◽  
pp. 204-218
Author(s):  
Yongzhang Zhou ◽  
Qianlong Zhang ◽  
Wenjie Shen ◽  
Fan Xiao ◽  
Yanlong Zhang ◽  
...  
Keyword(s):  
Porphyry Copper ◽  
Domain Ontology ◽  
Hangzhou Bay ◽  
Knowledge Graph ◽  
Construction Technology ◽  
Porphyry Copper Deposits ◽  
Metallogenic Province ◽  
Copper Deposits ◽  
Graph Language ◽  
Graph System

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.

scholarly journals Synospecies, an application to reflect changes in taxonomic names based on a triple store based on taxonomic data liberated from publication 

2021 ◽  
Vol 5 ◽  
Author(s):  
Reto Gmür ◽  
Donat Agosti
Keyword(s):  
Query Language ◽  
Building Blocks ◽  
Individual Treatment ◽  
Knowledge Graph ◽  
Triple Store ◽  
Related Group ◽  
Description Framework ◽  
Basic Vocabulary ◽  
User Friendly ◽  
Machine Readable

Taxonomic treatments, sections of publications documenting the features or distribution of a related group of organisms (called a “taxon”, plural “taxa”) in ways adhering to highly formalized conventions, and published in scientific journals, shape our understanding of global biodiversity (Catapano 2019). Treatments are the building blocks of the evolving scientific consensus on taxonomic entities. The semantics of these treatments and their relationships are highly structured: taxa are introduced, merged, made obsolete, split, renamed, associated with specimens and so on. Plazi makes this content available in machine-readable form using Resource Description Framework (RDF) . RDF is the standard model for Linked Data and the Semantic Web. RDF can be exchanged in different formats (aka concrete syntaxes) such as RDF/XML or Turtle. The data model describes graph structures and relies on Internationalized Resource Identifiers (IRIs) , ontologies such as Darwin Core basic vocabulary are used to assign meaning to the identifiers. For Synospecies, we unite all treatments into one large knowledge graph, modelling taxonomic knowledge and its evolution with complete references to quotable treatments. However, this knowledge graph expresses much more than any individual treatment could convey because every referenced entity is linked to every other relevant treatment. On synospecies.plazi.org, we provide a user-friendly interface to find the names and treatments related to a taxon. An advanced mode allows execution of queries using the SPARQL query language.

scholarly journals AN APPROACH TO EXTENDING QUERY SENTENCE FOR SEMANTIC ORIENTED SEARCH ON KNOWLEDGE GRAPH

2021 ◽  
Vol 50 (02) ◽  
Author(s):  
TẠ DUY CÔNG CHIẾN
Keyword(s):  
Relational Databases ◽  
Question Answering ◽  
Query Language ◽  
Knowledge Graph ◽  
Web Information Retrieval ◽  
Ontology Language ◽  
Description Framework ◽  
The Relationship ◽  
Resource Description ◽  
Terminological Confusion

There are many applications related to semantic web, information retrieval, information extraction, and question answering applying ontologies in recent years. To avoid the conceptual and terminological confusion, an ontology is built as a taxonomy ontology which identifies and distinguishes concepts as well as terminology. It accomplishes this by specifying a set of generic concepts that characterizes the domain as well as their definitions and interrelationships. There are some methods to represent ontologies, such as Resource Description Framework (RDF), Web Ontology Language (OWL), databases etc. depending on the characteristic of data. RDF, OWL usually is used the cases when data structure is objects which the relationship among the objects is simple. But if the relationship among the objects is more complex, using databases for storing ontologies is an approach to be better. However, using relational databases do not sufficiently support the semantic orientated search by Structured Query Language (SQL) and the searching speed is slow. Therefore, this paper introduces an approach to extending query sentences for semantic oriented search on knowledge graph.

scholarly journals Information Integration in a Mining Landscape

2017 ◽  
Vol 1 (2) ◽  
pp. 692-699 ◽  
Author(s):  
Gerald Hiebel ◽  
Klaus Hanke ◽  
Gert Goldenberg ◽  
Markus Staudt ◽  
Caroline Grutsch
Keyword(s):  
Bronze Age ◽  
Information Integration ◽  
Information Sources ◽  
Research Question ◽  
Knowledge Graph ◽  
Specific Information ◽  
Semantic Web Technologies ◽  
Mining Areas ◽  
Prehistoric Mining ◽  
Description Framework

The integration of information sources is a fundamental step to advance research and knowledge about the ancient mining landscape of Schwaz/Brixlegg in the Tyrol / Austria. The approach is applied for the localization, identification and interpretation of mining structures within the area. We want to show the use of the CIDOC CRM ontology with extensions in combination with a thesaurus to integrate data on a conceptual level. To implement this integration, we applied semantic web technologies to create a knowledge graph in RDF (Resource Description Framework) that currently represents the available information of seven different information sources in a network structure. More sources will be integrated using the same methodology. These are geochemical analysis of artefacts, onomastic research on names related to mining and archaeological information of other mining areas to research the spread of prehistoric mining activities and technologies.The RDF network can be queried for research, cultural or emergency response questions and the results can be displayed using Geoinformation systems. An exemplary archaeological research question is the location of mining, settlement and burial sites in the Bronze Age, differentiating between ore extraction, ore processing and smelting activities. For emergency forces the names and exact locations of mines are essential in case of an accident within an old mine. Different questions require a subset of the created knowledge graph. The results of queries to retrieve specific information can be visualised using appropriate tools.

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