Ontology-Based Context Modeling for Mobile Catering Recommendation

2013 ◽  
Vol 662 ◽  
pp. 953-956
Author(s):  
Dan Xiang Ai ◽  
Hui Zuo ◽  
Jun Yang
Keyword(s):  
Recommender System ◽  
Layer Structure ◽  
Domain Ontology ◽  
Use Case ◽  
Context Aware ◽  
Context Modeling ◽  
Specific Context ◽  
Contextual Model ◽  
Ontology Model ◽  
Upper Ontology

To support context-aware mobile recommendation, an ontology-based context modeling approach was proposed. We analyzed the framework of the mobile recommender system based on contextual model and suggested designing the model with two-layer structure including an upper ontology layer and a domain ontology layer. The ontologies provides formalizations representing the main entities, including users, objects, contexts, and their interactive relationships in mobile recommendation environments. A specific context ontology model for catering recommendation was developed and a use case of the instantiated context ontology was demonstrated.

Context Ontology Modeling for Mobile Petrol Station Recommendation

2013 ◽  
Vol 291-294 ◽  
pp. 2849-2852
Author(s):  
Hui Zuo ◽  
Dan Xiang Ai
Keyword(s):  
Domain Ontology ◽  
Use Case ◽  
Context Modeling ◽  
Petrol Station ◽  
Modeling Approach ◽  
Ontology Modeling ◽  
Ontology Model ◽  
Upper Ontology

To support the personalized mobile recommendation service, a context modeling approach based on ontology was proposed. The role of context ontologies in mobile recommenders was discussed, and under the application background of petrol station recommendation, a two-level context ontology model was designed. The model contains an upper ontology to describe general concepts, and a domain ontology extended from the upper ontology. The context ontology provides formalizations representing the mainly entities including users, objects and contexts, and their interactive relationships in mobile recommendation environments. Finally, a use case of the instantiated context ontology was demonstrated.

Intelligent Petrol Station Recommender Based on Context Ontology and Rule Inference

2013 ◽  
Vol 303-306 ◽  
pp. 1412-1415
Author(s):  
Hui Zuo ◽  
Dan Xiang Ai ◽  
Jun Yang
Keyword(s):  
Recommender System ◽  
Domain Ontology ◽  
Petrol Station ◽  
Ontology Modeling ◽  
Ontology Model ◽  
Rule Inference ◽  
Upper Ontology

An intelligent mobile petrol station recommender system based on context ontology and rule inference is deigned. The approach of context ontology modeling specific for mobile recommendation is discussed. And a two-level context ontology model including upper ontology and domain ontology used in petrol station recommender is developed. The generation of recommendation rules based on the context ontologies and the process of the rule inference for recommendation are also demonstrated.

Mining Context History for Generating User Models for Proactive Personalized Mobile Networking Applications

2013 ◽  
Vol 411-414 ◽  
pp. 638-642
Author(s):  
Wei An ◽  
Qi Hua Liu
Keyword(s):  
Recommender System ◽  
Research Field ◽  
Context Aware ◽  
System Framework ◽  
Specific Context ◽  
User Models ◽  
Mobile Networking ◽  
Personalized Services ◽  
Context Aware System ◽  
Ubiquitous Networking

Context history has a concrete role to play in supporting proactive personalized services in a mobile and ubiquitous networking environment. However, despite its promise, the utilization of context history in this way is a relatively under-explored research field. This paper proposed a context-aware system framework for proactive personalized mobile networking applications based on user models utilizing the context history. Based on the proposed framework, we presented a system called CAMTRS, which was an context-aware mobile tourism recommender system that serves a tourist with information needed in his specific context that are interesting to him given his goal for that moment. From our experiment and evaluation, the proposed framework is a promising approach to provider proactive personalized services to mobile users.

Personalized Mobile Catering Recommender System Based on Context Ontology Model and Rule Inference

2013 ◽  
Vol 717 ◽  
pp. 708-713 ◽  
Author(s):  
Dan Xiang Ai ◽  
Hui Zuo ◽  
Jun Yang
Keyword(s):  
Pervasive Computing ◽  
Recommender System ◽  
Personalized Recommendation ◽  
Context Aware ◽  
Rule Generation ◽  
Context Model ◽  
Ontology Modeling ◽  
Ontology Model ◽  
Smart Mobile ◽  
Rule Inference

With the development of smart mobile terminals and pervasive computing, mobile recommender systems are proposed to realize context-aware personalized recommendation services. A context model plays a key role in a mobile recommender. We discussed the context ontology modeling approach specific for mobile recommendation, and developed a two-level context model including a upper ontology and a domain ontology. We also designed a personalized mobile catering recommender system based on the context ontology model and rule inference. The framework of the system is depicted. And the process of rule generation and rule inference based on the context ontologies is demonstrated.

Case Base Elicitation for a Context-Aware Recommender System

2018 ◽  
pp. 170-185
Author(s):  
Jose Luis Jorro-Aragoneses ◽  
Guillermo Jimenez-Díaz ◽  
Juan Antonio Recio-García ◽  
Belén Díaz-Agudo
Keyword(s):  
Recommender System ◽  
Context Aware ◽  
Case Base

scholarly journals Context-Aware Recommender System: A Review of Recent Developmental Process and Future Research Direction

2017 ◽  
Vol 7 (12) ◽  
pp. 1211 ◽  
Author(s):  
Khalid Haruna ◽  
Maizatul Akmar Ismail ◽  
Suhendroyono Suhendroyono ◽  
Damiasih Damiasih ◽  
Adi Pierewan ◽  
...  
Keyword(s):  
Recommender System ◽  
Developmental Process ◽  
Research Direction ◽  
Future Research ◽  
Context Aware ◽  
Future Research Direction ◽  
System A

scholarly journals Context-aware Music Recommender System Based on Implicit Feedback

2021 ◽  
Vol 36 (1) ◽  
pp. WI2-D_1-10
Author(s):  
Yasufumi Takama ◽  
Jing-cheng Zhang ◽  
Hiroki Shibata
Keyword(s):  
Recommender System ◽  
Implicit Feedback ◽  
Context Aware

scholarly journals Preserving User Privacy and Security in Context-Aware Mobile Platforms

2019 ◽  
pp. 1203-1230 ◽  
Author(s):  
Prajit Kumar Das ◽  
Dibyajyoti Ghosh ◽  
Pramod Jagtap ◽  
Anupam Joshi ◽  
Tim Finin
Keyword(s):  
Context Aware ◽  
Context Modeling ◽  
User Privacy ◽  
Mobile Platforms ◽  
Privacy And Security ◽  
Semantic Web Technologies ◽  
Fine Grained ◽  
New Class ◽  
Context Data ◽  
Collaborative Context

Contemporary smartphones are capable of generating and transmitting large amounts of data about their users. Recent advances in collaborative context modeling combined with a lack of adequate permission model for handling dynamic context sharing on mobile platforms have led to the emergence of a new class of mobile applications that can access and share embedded sensor and context data. Most of the time such data is used for providing tailored services to the user but it can lead to serious breaches of privacy. We use Semantic Web technologies to create a rich notion of context. We also discuss challenges for context aware mobile platforms and present approaches to manage data flow on these devices using semantically rich fine-grained context-based policies that allow users to define their privacy and security need using tools we provide.

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

2021 ◽  
Vol 24 (1) ◽  
pp. 507
Author(s):  
Hussein Ali Ahmed Ghanim ◽  
László Kovács
Keyword(s):  
Learning Process ◽  
Time Management ◽  
Application Programming Interface ◽  
Domain Ontology ◽  
Actual Process ◽  
Process Ontology ◽  
Support Mechanism ◽  
Ontology Language ◽  
Ontology Model ◽  
E Learning

<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>

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