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[PDF][PDF] Ontology construction from text: challenges and trends
A Al-Arfaj, AM Al-Salman - … Journal of Artificial Intelligence and Expert …, 2015 - Citeseer
Ontology is one of the most popular representation model used for knowledge
representation, sharing and reusing. In light of the importance of ontology, different …
representation, sharing and reusing. In light of the importance of ontology, different …
A design for additive manufacturing ontology
Design for additive manufacturing (DFAM) gives designers new freedoms to create complex
geometries and combine parts into one. However, it has its own limitations, and more …
geometries and combine parts into one. However, it has its own limitations, and more …
Approaches for simulation model reuse in systems design—A review
In this paper, we review the literature related to the reuse of computer-based simulation
models in the context of systems design. Models are used to capture aspects of existing or …
models in the context of systems design. Models are used to capture aspects of existing or …
[KİTAP][B] Semantic modeling for data
P Alexopoulos - 2020 - books.google.com
What value does semantic data modeling offer? As an information architect or data science
professional, let's say you have an abundance of the right data and the technology to extract …
professional, let's say you have an abundance of the right data and the technology to extract …
Ontology learning methods from text-an extensive knowledge-based approach
J Wątróbski - Procedia Computer Science, 2020 - Elsevier
Ontologies are a key element of the Semantic Web. They aim to capture basic knowledge by
providing appropriate terms and formal relationships between them, so that they can be …
providing appropriate terms and formal relationships between them, so that they can be …
Handling uncertainty in self-adaptive systems: an ontology-based reinforcement learning model
Ubiquitous and pervasive systems interact with each other and perform actions favoring the
emergence of a global desired behavior. To function well, these systems need to be self …
emergence of a global desired behavior. To function well, these systems need to be self …
Context-aware recommender for mobile learners
R Benlamri, X Zhang - Human-centric Computing and Information …, 2014 - Springer
As mobile technologies become widespread, new challenges are facing the research
community to develop lightweight learning services adapted to the learner's profile, context …
community to develop lightweight learning services adapted to the learner's profile, context …
Semantic variance: an intuitive measure for ontology accuracy evaluation
Ontology evaluation is a relevant issue in the field of knowledge representation. It aims at
quantifying the quality of ontologies, so that potential users can have an idea of their …
quantifying the quality of ontologies, so that potential users can have an idea of their …
[HTML][HTML] Advancing Sustainable Manufacturing: Reinforcement Learning with Adaptive Reward Machine Using an Ontology-Based Approach
Sustainable manufacturing practices are crucial in job shop scheduling (JSS) to enhance
the resilience of production systems against resource shortages and regulatory changes …
the resilience of production systems against resource shortages and regulatory changes …
Information extraction in illicit web domains
Extracting useful entities and attribute values from illicit domains such as human trafficking is
a challenging problem with the potential for widespread social impact. Such domains …
a challenging problem with the potential for widespread social impact. Such domains …