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Design and Implementation of Adaptive Recommendation System
2018
International journal of management, technology, and social science
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The semantic and recommendation and personalized search of Learning objects is based on the comparison of the learner profile and learning objects to determine a more suitable relationship between learning ...
E-learning offers advantages for E-learners by making access to learning objects at any time or place, very fast, just-in-time and relevance. ...
The semantic and personalized search of the learning content is based on comparison of the learner profile and learning object to determine a International Journal of Management, Technology, and Social ...
doi:10.47992/ijmts.2581.6012.0039
fatcat:q7v45hjw5rh2zngasw7avvu4qa
Design And Implementation Of Adaptive Recommendation System
2018
Zenodo
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The semantic and recommendation and personalized search of Learning objects is based on the comparison of the learner profile and learning objects to determine a more suitable relationship between learning ...
E-learning offers advantages for E-learners by making access to learning objects at any time or place, very fast, just-in-time and relevance. ...
The semantic and personalized search of the learning content is based on comparison of the learner profile and learning object to determine a
International Journal of Management, Technology, and Social ...
doi:10.5281/zenodo.1254142
fatcat:li4axbfdrzccdlttf5kpvalnry
Toward Social Media Content Recommendation Integrated with Data Science and Machine Learning Approach for E-Learners
2020
Symmetry
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This application demonstrated the need and success of e-learning software that is linked with social media and sends recommendations for the content being learned by the e-Learners in the e-learning environment ...
For recommendations, a Reinforcement learning model with optimization is employed, which utilizes the learners' local context, learners' profile available in the e-learning system, and the learners' historical ...
• The main objective of this study is the use of data mining and machine learning approaches for social media content recommendation. ...
doi:10.3390/sym12111798
fatcat:wfgccritmjgn7lopmy7yz7dxna
Agent-Based Recommendation in E-Learning Environment Using Knowledge Discovery and Machine Learning Approaches
2022
Mathematics
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E-learning is a popular area in terms of learning from social media websites in various terms and contents for every group of people in this world with different knowledge backgrounds and jobs. ...
We applied Natural Language Processing (NLP) techniques and semantic analysis approaches for the recommendation of course selection to e-learners and tutors. ...
Conclusions A recommendation system is one of the important aspects of a machine learning system. ...
doi:10.3390/math10071192
fatcat:ondayfs57bdgbpu2xwoeflbqcq
A Systematic Mapping Review on MOOC Recommender Systems
2021
IEEE Access
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Machine learning techniques were also adopted for resource recommendation in the literature. Hmedna et al. ...
Machine learning algorithms have also played role in Social recommendation as Williams et al. [77] used thomas sampling for email recommendation, Rahma and Kouthe air [139] proposed random forest for ...
doi:10.1109/access.2021.3101039
fatcat:vnhraonfujgstdvcnpcwi6lxxe
A Smart Access Control Method for Online Social Networks Based on Support Vector Machine
2020
IEEE Access
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INDEX TERMS Online social networks, access control method, support vector machine, machine learning. 11096 This work is licensed under a Creative Commons Attribution 4.0 License. ...
With the rapid development of Internet technology, online social networks (OSNs) has become one of the main ways for people to develop social activities. ...
ACKNOWLEDGMENT The authors would like to thank the editor and the anonymous referees for their constructive comments. ...
doi:10.1109/access.2020.2963932
fatcat:nvrs5dlyajarji4v63yk4acsjq
Guest editorial: social media for personalization and search
2019
Information retrieval (Boston)
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Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ...
Acknowledgements We thank all the authors for considering this special issue as an outlet to publish their research results in the area of social media for personalization and search. ...
Finally, we express our gratitude to the Editors-in-Chief, for their kind support, advice, and encouragements throughout the preparation of this special issue. ...
doi:10.1007/s10791-019-09352-1
fatcat:vxrqidy7x5fzhbcw6jfyxyqc24
Intelligent Methods for Big Data Analytics and Cyber Security
2018
Information & Security An International Journal
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It presents and compares big data analysis techniques such as quantitative analysis, qualitative analysis, data mining, statistical analysis, machine learning, semantic analysis, and visual analysis. ...
The importance and prospects of intelligent methods for big data analysis are emphasized. ...
In this article, machine learning and its relation to data mining are studied through the scope of the following types of machine learning techniques: classification, clustering, outlier detection and ...
doi:10.11610/isij.3921
fatcat:ctvamznorbfb7j7oxolvhh54ci
A Rule Based System to Refine User Walls
2015
International Journal on Recent and Innovation Trends in Computing and Communication
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This allows users to customize the refining criteria to be applied to their walls, and a Machine Learning-based classifier automatically classifies the messages and labelling messages in support of content-based ...
The core problem in today's Online Social Networks (OSNs) is to allocate users the authority to manage the messages posted on their private space to avert that unwanted content. ...
In the research community the dominant approach to this problem is based on machine learning techniques: a general inductive process automatically builds a classifier by learning, from a set of pre classified ...
doi:10.17762/ijritcc2321-8169.150229
fatcat:e4ujm2dwlvh5bj3nzjicjb6b34
Efficient Context Management and Personalized User Recommendations in a Smart Social TV Environment
[chapter]
2017
Lecture Notes in Computer Science
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in the context of a Dynamic Social & Media Content Syndication (SAM) platform. ...
With the emergence of Smart TV and related interconnected devices, second screen solutions have rapidly appeared to provide more content for end-users and enrich their TV experience. ...
Beyond comparing SAM Context Management approach with other machine learning techniques in terms of effectiveness, we also present a comparison of the two algorithms running on top of the graph database ...
doi:10.1007/978-3-319-61920-0_8
fatcat:mr6xl5as4zhk5a4biqh5x5o4qe
A Conceptual Model for the E-Commerce Application Recommendation Framework using Exploratory Search
2020
Journal of Computer Science
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This research work aims to create a conceptual model for recommendation systems using exploratory search, to study the behavior of users and the efficacy of exploratory search in terms of the quality of ...
To boost the user's search for product recommendations, use a search engine for the quest but not for purchasing purposes. ...
It showed that, in e-commerce applications, there is a lack of a strong recommender program with a better search experience. ...
doi:10.3844/jcssp.2020.1163.1171
fatcat:ykky5i4girbvlkp5gdkofihug4
Designing for effective end-user interaction with machine learning
2011
Proceedings of the 24th annual ACM symposium adjunct on User interface software and technology - UIST '11 Adjunct
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system called ReGroup that employs end-user interactive machine learning for the purpose of access control in social networks, (3) a novel system called CueT that supports end-user driven machine learning ...
Specifically, this dissertation presents (1) new interaction techniques for end-user creation of image classifiers in an existing end-user interactive machine learning system called CueFlik, (2) a novel ...
I also want to thank my bonus advisor, Desney Tan, for his unwavering encouragement. His insight and drive continues to inspire me. ...
doi:10.1145/2046396.2046416
dblp:conf/uist/Amershi11
fatcat:q3ticzzymngu5i7uhdcyshmt34
Machine Learning or Information Retrieval Techniques for Bug Triaging: Which is better?
2017
e-Informatica Software Engineering Journal
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The results of the study show that the information retrieval based technique yields better efficiency in recommending the developers for bug reports. ...
A deeper investigation has shown that the trend of techniques is taking a shift from machine learning based approaches towards information retrieval based approaches. ...
[38] merged information retrieval with a machine learning based technique for effective developer recommendation. ...
doi:10.5277/e-inf170106
dblp:journals/eInformatica/GoyalS17a
fatcat:hbhpl5rqdvavloikcx2fgjcklq
On the benefit of logic-based machine learning to learn pairwise comparisons
2020
Bulletin of Electrical Engineering and Informatics
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In recent years, many daily processes such as internet web searching, e-mail filtering, social media services, e-commerce have benefited from machine learning techniques (ML). ...
In this paper, we propose the use of a logic-based approach to learn user preference in the form of pairwise comparisons. ...
The contribution of this paper includes: (1) implementing our novel logic based machine learning approach for a real-life recommender system, (2) introducing the use of pairwise preference in recommender ...
doi:10.11591/eei.v9i6.2384
fatcat:eleo4bfwqjcl5owtt7molbo7xm
Social media intention mining for sustainable information systems: categories, taxonomy, datasets and challenges
2021
Complex & Intelligent Systems
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The analysis reveals that there exist eight prominent categories of intention. Furthermore, a taxonomy of the approaches and techniques used for intention mining have been discussed in this article. ...
Search engines are a major source to infer users' past searching activities to predict their intention, facilitating the vendors and manufacturers to present their products to the user in a promising manner ...
As contrasted to the other studies, this SLR presented a taxonomy to map the state-of-the-art techniques such as machine learning, deep learning, image processing, and statistical techniques for intention ...
doi:10.1007/s40747-021-00342-9
fatcat:ak3y4ao2sbffjd5b3rbttidvjy
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