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.

Design of Smart Space Context-aware System Framework

2013 ◽  
Vol 12 (20) ◽  
pp. 5616-5620 ◽  
Author(s):  
Wang Xiao-chi ◽  
Xu Jie ◽  
Fang Zhi-gang
Keyword(s):  
Context Aware ◽  
Smart Space ◽  
System Framework ◽  
Context Aware System

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.

Toward a Hybrid Recommender System for E-learning Personnalization Based on Data Mining Techniques

2018 ◽  
Vol 2 (4) ◽  
pp. 271 ◽  
Author(s):  
Outmane Bourkoukou ◽  
Essaid El Bachari
Keyword(s):  
Learning Style ◽  
Recommender System ◽  
Adaptive Learning ◽  
Learning Objects ◽  
Research Field ◽  
Learning System ◽  
K Nearest Neighbors ◽  
E Learning ◽  
Hybrid Recommender System ◽  
Hybrid Recommender

Personalized courseware authoring based on recommender system, which is the process of automatic learning objects selecting and sequencing, is recognized as one of the most interesting research field in intelligent web-based education. Since the learner’s profile of each learner is different from one to another, we must fit learning to the different needs of learners. In fact from the knowledge of the learner’s profile, it is easier to recommend a suitable set of learning objects to enhance the learning process. In this paper we describe a new adaptive learning system-LearnFitII, which can automatically adapt to the dynamic preferences of learners. This system recognizes different patterns of learning style and learners’ habits through testing the psychological model of learners and mining their server logs. Firstly, the device proposed a personalized learning scenario to deal with the cold start problem by using the Felder and Silverman’s model. Next, it analyzes the habits and the preferences of the learners through mining the information about learners’ actions and interactions. Finally, the learning scenario is revisited and updated using hybrid recommender system based on K-Nearest Neighbors and association rule mining algorithms. The results of the system tested in real environments show that considering the learner’s preferences increases learning quality and satisfies the learner.

Algorithms for Rule Generation and Matchmaking in Context-Aware System

2009 ◽  
Vol 20 (10) ◽  
pp. 2655-2666 ◽  
Author(s):  
Dong LIU ◽  
Xiang-Wu MENG ◽  
Jun-Liang CHEN ◽  
Ya-Mei XIA
Keyword(s):  
Context Aware ◽  
Rule Generation ◽  
Context Aware System

scholarly journals A Survey on Blockchain-Based Search Engines

2021 ◽  
Vol 11 (15) ◽  
pp. 7063
Author(s):  
Esmaeel Rezaee ◽  
Ali Mohammad Saghiri ◽  
Agostino Forestiero
Keyword(s):  
Search Engines ◽  
Research Field ◽  
The Internet ◽  
Context Aware ◽  
Search System ◽  
Search Results ◽  
Related Information ◽  
Research Article ◽  
Different Types ◽  
Search History

With the increasing growth of different types of data, search engines have become an essential tool on the Internet. Every day, billions of queries are run through few search engines with several privacy violations and monopoly problems. The blockchain, as a trending technology applied in various fields, including banking, IoT, education, etc., can be a beneficial alternative. Blockchain-based search engines, unlike monopolistic ones, do not have centralized controls. With a blockchain-based search system, no company can lay claims to user’s data or access search history and other related information. All these data will be encrypted and stored on a blockchain. Valuing users’ searches and paying them in return is another advantage of a blockchain-based search engine. Additionally, in smart environments, as a trending research field, blockchain-based search engines can provide context-aware and privacy-preserved search results. According to our research, few efforts have been made to develop blockchain use, which include studies generally in the early stages and few white papers. To the best of our knowledge, no research article has been published in this regard thus far. In this paper, a survey on blockchain-based search engines is provided. Additionally, we state that the blockchain is an essential paradigm for the search ecosystem by describing the advantages.

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