scholarly journals Тhe semantic ontology in Wittgenstein’s philosophy

2020 ◽  
Author(s):  
Denitsa Zhelyazkova
Keyword(s):  
Semantic Ontology

Automatic Extraction of Semantic Relations from Wikipedia

2015 ◽  
Vol 24 (02) ◽  
pp. 1540010 ◽  
Author(s):  
Patrick Arnold ◽  
Erhard Rahm
Keyword(s):  
Finite State Machines ◽  
Background Knowledge ◽  
Semantic Relations ◽  
Automatic Extraction ◽  
State Machines ◽  
High Quality ◽  
Novel Approach ◽  
Finite State ◽  
Semantic Ontology

We introduce a novel approach to extract semantic relations (e.g., is-a and part-of relations) from Wikipedia articles. These relations are used to build up a large and up-to-date thesaurus providing background knowledge for tasks such as determining semantic ontology mappings. Our automatic approach uses a comprehensive set of semantic patterns, finite state machines and NLP techniques to extract millions of relations between concepts. An evaluation for different domains shows the high quality and effectiveness of the proposed approach. We also illustrate the value of the newly found relations for improving existing ontology mappings.

scholarly journals Intelligent Identification of Trademark Case Precedents Using Semantic Ontology

2020 ◽  
Author(s):  
A.S. Li ◽  
A.J.C. Trappey ◽  
C.V. Trappey
Keyword(s):  
Clustering Algorithm ◽  
Latent Dirichlet Allocation ◽  
Semantic Analysis ◽  
Semantic Network ◽  
Federal Courts ◽  
Computer Assisted ◽  
Legal Action ◽  
Legal Cases ◽  
Semantic Ontology ◽  
Machine Readable

A registered trademark distinctively identifies a company, its products or services. A trademark (TM) is a type of intellectual property (IP) which is protected by the laws in the country where the trademark is officially registered. TM owners may take legal action when their IP rights are infringed upon. TM legal cases have grown in pace with the increasing number of TMs registered globally. In this paper, an intelligent recommender system automatically identifies similar TM case precedents for any given target case to support IP legal research. This study constructs the semantic network representing the TM legal scope and terminologies. A system is built to identify similar cases based on the machine-readable, frame-based knowledge representations of the judgments/documents. In this research, 4,835 US TM legal cases litigated in the US district and federal courts are collected as the experimental dataset. The computer-assisted system is constructed to extract critical features based on the ontology schema. The recommender will identify similar prior cases according to the values of their features embedded in these legal documents which include the case facts, issues under disputes, judgment holdings, and applicable rules and laws. Term frequency-inverse document frequency is used for text mining to discover the critical features of the litigated cases. Soft clustering algorithm, e.g., Latent Dirichlet Allocation, is applied to generate topics and the cases belonging to these topics. Thus, similar cases under each topic are identified for references. Through the analysis of the similarity between the cases based on the TM legal semantic analysis, the intelligent recommender provides precedents to support TM legal action and strategic planning.

Balinese Kulkul Semantic Ontology: REST API Mobile Application Development

2021 ◽  
Vol 9 (4) ◽  
pp. 457
Author(s):  
I Putu Agus Wahyu Widiatmika ◽  
Cokorda Rai Adi Pramartha
Keyword(s):  
Web Service ◽  
Mobile Technology ◽  
Mobile Applications ◽  
Mobile Application ◽  
Word Of Mouth ◽  
Cultural Knowledge ◽  
Application Development ◽  
Technological Developments ◽  
Semantic Ontology ◽  
Rest Api

Kulkul is one of Bali's cultural heritage. Kulkul is used in Balinese society for communication when there is a danger, death, a ritual, and so on. The current phenomenon is that many Balinese people are only able to know and without knowing much knowledge about kulkul. It is because this knowledge is the only word of mouth, making it difficult for it to be collected, stored, retrieved, shared, and renewed. Current technological developments, especially mobile technology, allow the development of mobile applications on cultural knowledge with an ontology approach that will help provide an explicit explanation of this knowledge. In this study, the authors propose the application of a web service with a REST API architecture to help mobile applications integrate Balinese Kulkul Semantic Ontology. This study uses the prototyping method in developing the REST API. From the tests that have been done, it is found that the REST API has successfully received requests and responses which prove that the mobile application is well integrated.

Research on literary intelligent translation based on improved optimization model

2021 ◽  
pp. 1-7
Author(s):  
Hongjian Liu
Keyword(s):  
Neural Network ◽  
Machine Translation ◽  
Optimization Model ◽  
Daily Life ◽  
Literary Translation ◽  
Semantic Features ◽  
Network Layer ◽  
Training Time ◽  
Semantic Ontology ◽  
Important Position

Machine translation is widely used in people’s daily life and production, occupying an important position. In order to improve the accuracy of literary intelligent translation, this study explores literary intelligent translation based on improved optimization model. According to semantic features, machine translation was used to create a semantic ontology optimization model that includes an encoder and a decoder, and a conversion layer including a forward neural network layer, a residual connection and a normalization layer were added to the semantic ontology optimization model between the encoder and the decoder, the conversion layer was used to achieve grammatical conversion, which improves the accuracy of intelligent translation of the semantic ontology optimization model. Results show that the BLEU value of using this method to translate literary sentences can reach 17.23 when the number of training steps is 8000, and the training time is low, the translation result has a low correlation misalignment rate, which can meet the user’s literary translation needs.

An Ontology based on the Methodology Proposed by Ushold and King

2016 ◽  
Vol 7 (1) ◽  
pp. 13-26 ◽  
Author(s):  
Neha Jain ◽  
Lalit Sen Sharma
Keyword(s):  
Software Development ◽  
Ontology Engineering ◽  
Ontology Development ◽  
Semantic Technologies ◽  
Domain Specific ◽  
Development Processes ◽  
Ontology Building ◽  
Software Development Methodologies ◽  
Semantic Ontology ◽  
Standard Software

A number of methodologies are available in literature for ontology development but as the Ontology engineering field is relatively new, it is still unclear how the existing ontology building methodologies can be applied to develop semantic ontology models. In this work, firstly an overview of various ontology building methodologies and their limitations as compared to some standard software development methodologies are presented. Then the methodology proposed by Ushold and King is selected to build an ontology in e-banking domain. The challenge in this domain is to recognize, communicate and steadily improvise the banking solutions. The ontologies are prospective candidates to assist overcome these challenges and enhance interoperability of banking data and services. The study aims to provide direction for the application of existing ontology building methodologies in the Semantic Web Development processes of e-banking domain specific models which would enable their reusability and repeatability in other projects and strengthen the adoption of semantic technologies in the domain.

scholarly journals Balancing Timing and Accuracy Requirements in Human Activity Recognition Mobile Applications

Proceedings ◽  
2019 ◽  
Vol 31 (1) ◽  
pp. 15
Author(s):  
Roua Jabla ◽  
Félix Buendía ◽  
Maha Khemaja ◽  
Sami Faiz
Keyword(s):  
Activity Recognition ◽  
Human Activity ◽  
Response Times ◽  
Main Idea ◽  
Human Activity Recognition ◽  
User Interactions ◽  
Machine Learning Classification ◽  
Ambient Intelligent ◽  
Current Context ◽  
Semantic Ontology

Timing requirements are present in many current context-aware and ambient intelligent applications. These kinds of applications usually demand a timing response according to needs dealing with context changes and user interactions. The current work introduces an approach that combines knowledge-driven and data-driven methods to check these requirements in the area of human activity recognition. Such recognition is traditionally based on machine learning classification algorithms. Since these algorithms are highly time consuming, it is necessary to choose alternative approaches when timing requirements are tight. In this case, the main idea consists of taking advantage of semantic ontology models that allow maintaining a level of accuracy during the recognition process while achieving the required response times. The experiments performed and their results in terms of checking such timing requirements along with keeping acceptable recognition levels confirm this idea as shown in the final section of the work.

A framework for disease diagnosis based on fuzzy semantic ontology approach

2020 ◽  
Vol 12 (5) ◽  
pp. 475
Author(s):  
Nora Shoaip ◽  
Shaker El Sappagh ◽  
Sherif Barakat ◽  
Mohammed Elmogy
Keyword(s):  
Disease Diagnosis ◽  
Semantic Ontology
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