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Articles 1 - 14 of 14
Full-Text Articles in Engineering
Personalizing Student Graduation Paths Using Expressed Student Interests, Nicolas Dobbins, Ali R. Hurson, Sahra Sedigh
Personalizing Student Graduation Paths Using Expressed Student Interests, Nicolas Dobbins, Ali R. Hurson, Sahra Sedigh
Electrical and Computer Engineering Faculty Research & Creative Works
This paper proposes an intelligent recommendation approach to facilitate personalized education and help students in planning their path to graduation. The goal is to identify a path that aligns with a student's interests and career goals and approaches optimality with respect to one or more criteria, such as time-to-graduation or credit hours taken. The approach is illustrated and verified through application to undergraduate curricula at the Missouri University of Science and Technology.
True-Ed Select: A Machine Learning Based University Selection Framework, Jerry C. Cearley
True-Ed Select: A Machine Learning Based University Selection Framework, Jerry C. Cearley
University of the Pacific Theses and Dissertations
University/College selection is a daunting task for young adults and their parents alike. This research presents True-Ed Select, a machine learning framework that simplifies the college selection process. The framework uses a four-layered approach including the user survey, machine learning, consolidation, and recommendation. The first layer collects both the objective and subjective attributes from users that best characterize their ideal college experience. The second layer employs machine learning techniques to analyze the objective and subjective attributes. The third layer combines the results from the machine learning techniques. The fourth layer inputs the consolidated result and presents a user-friendly list of …
Dynamics Of Running Processes In The Area Of Underless Water Intake, D.R. Bazarov, M.P. Tashkhanova, A. Gayur, M. Sapaeva
Dynamics Of Running Processes In The Area Of Underless Water Intake, D.R. Bazarov, M.P. Tashkhanova, A. Gayur, M. Sapaeva
Irrigation and Melioration
The paper analyzes the dynamics of channel processes based on the results of field studies of the Amudarya River at the site of the damless water intake to the Karshi Magistralny Canal (KMK) and developed recommendations for improving the water intake conditions. Based on the results of field studies of the head section of the inlet channel, an assessment of the state of the Amudarya river bed in the water intake zone was made. The results of studies of the hydraulic and alluvial regimes of the Amu Darya River in the area of the damless water intake are generalized The …
Multiplex Memory Network For Collaborative Filtering, Xunqiang Jiang, Binbin Hu, Yuan Fang, Chuan Shi
Multiplex Memory Network For Collaborative Filtering, Xunqiang Jiang, Binbin Hu, Yuan Fang, Chuan Shi
Research Collection School Of Computing and Information Systems
Recommender systems play an important role in helping users discover items of interest from a large resource collection in various online services. Although current deep neural network-based collaborative filtering methods have achieved state-of-the-art performance in recommender systems, they still face a few major weaknesses. Most importantly, such deep methods usually focus on the direct interaction between users and items only, without explicitly modeling high-order co-occurrence contexts. Furthermore, they treat the observed data uniformly, without fine-grained differentiation of importance or relevance in the user-item interactions and high-order co-occurrence contexts. Inspired by recent progress in memory networks, we propose a novel multiplex …
From Ideal To Reality: Segmentation, Annotation, And Recommendation, The Vital Trajectory Of Intelligent Micro Learning, Jiayin Lin, Geng Sun, Tingru Cui, Jun Shen, Dongming Xu, Ghassan Beydoun, Ping Yu, David Pritchard, Li Li, Shiping Chen
From Ideal To Reality: Segmentation, Annotation, And Recommendation, The Vital Trajectory Of Intelligent Micro Learning, Jiayin Lin, Geng Sun, Tingru Cui, Jun Shen, Dongming Xu, Ghassan Beydoun, Ping Yu, David Pritchard, Li Li, Shiping Chen
Faculty of Engineering and Information Sciences - Papers: Part B
The soaring development of Web technologies and mobile devices has blurred time-space boundaries of people’s daily activities. Such development together with the life-long learning requirement give birth to a new learning style, micro learning. Micro learning aims to effectively utilize learners’ fragmented time to carry out personalized learning activities through online education resources. The whole workflow of a micro learning system can be separated into three processing stages: micro learning material generation, learning materials annotation and personalized learning materials delivery. Our micro learning framework is firstly introduced in this paper from a higher perspective. Then we will review representative segmentation …
Pairwise-Based Hierarchical Gating Networks For Sequential Recommendation, Kexin Huang, Ye Du, Li Li, Jun Shen, Geng Sun
Pairwise-Based Hierarchical Gating Networks For Sequential Recommendation, Kexin Huang, Ye Du, Li Li, Jun Shen, Geng Sun
Faculty of Engineering and Information Sciences - Papers: Part B
The sequential pattern behind users’ behaviors indicates the importance of exploring the transition relationships among adjacent items in next-item recommendation task. Most existing methods based on Markov Chains or deep learning architecture have demonstrated their superiority in sequential recommendation scenario, but they have not been well-studied at a range of problems: First, the influence strength of items that the user just access might be different since not all items are equally important for modeling user’s preferences. Second, the user might assign various interests to certain parts of items, as what often attracts users is a specific feature or aspect of …
Hybrid Translation And Language Model For Micro Learning Material Recommendation, Jiayin Lin
Hybrid Translation And Language Model For Micro Learning Material Recommendation, Jiayin Lin
Faculty of Engineering and Information Sciences - Papers: Part A
As an emerging pedagogy, micro learning aims to make use of people’s fragmented spare time and provide personalized online learning service, for example, by pushing fragmented knowledge to specific learners. In the context of big data, the recommender system is the key factor for realizing the online personalization service, which significantly determines what information will be fmally accessed by the target learners. In the education discipline, due to the pedagogical requirements and the domain characteristics, ranking recommended learning materials is essential for maintaining the outcome of the massive learning scenario. However, many widely used recommendation strategies in other domains showed …
Trust Model And Simulation Of E-Commerce Based On Social Networks, Yu Zhen, Zhu Jie, Guicheng Shen
Trust Model And Simulation Of E-Commerce Based On Social Networks, Yu Zhen, Zhu Jie, Guicheng Shen
Journal of System Simulation
Abstract: In the current e-commerce industry, users need to check for the historical evaluation of the commodity before buying goods mostly, but false recommendations and massive redundancy recommendation problem which widely exists at present seriously affect the effectiveness and accuracy of users’ obtaining recommendations. For getting trust in e-commerce transactions, an e-commerce trust model SNTrust based on social networks is proposed. In SNTrust model, each user maintains a trusted social network set; a topological structure of the user information diffusion in the social network is described in the model, and the recommendation node trust is introduced to measure its credibility, …
Organizing Online Computation For Adaptive Micro Open Education Resource Recommendation, Geng Sun, Tingru Cui, Ghassan Beydoun, Shiping Chen, Dongming Xu, Jun Shen
Organizing Online Computation For Adaptive Micro Open Education Resource Recommendation, Geng Sun, Tingru Cui, Ghassan Beydoun, Shiping Chen, Dongming Xu, Jun Shen
Faculty of Engineering and Information Sciences - Papers: Part B
Our previous work, Micro Learning as a Service (MLaaS), aimed to deliver adaptive micro open education resources (OERs). However, relying solely on the offline computation, the recommendation lacks rationality and timeliness. It is also difficult to make the first recommendation to a new learner. In this paper we introduce the organization of the online computation of the MLaaS. It targets at solving the cold start problem due to the shortage of learner information and real-time updates of the learner-micro OER profile
Msis 2016: A Comprehensive Update Of Graduate Level Curriculum Recommendation In Information Systems, Heikki Topi, Susan A. Brown, Joao Alvaro Carvalho, Brian Donnellan, Helena Karsten, Jun Shen, Bernard C. Y Tan, Mark F. Thouin
Msis 2016: A Comprehensive Update Of Graduate Level Curriculum Recommendation In Information Systems, Heikki Topi, Susan A. Brown, Joao Alvaro Carvalho, Brian Donnellan, Helena Karsten, Jun Shen, Bernard C. Y Tan, Mark F. Thouin
Faculty of Engineering and Information Sciences - Papers: Part A
The process to revise MSIS 2006, the master's level curriculum recommendation for Information Systems, is getting close to completion. In spring and summer 2016, the joint AIS/ACM task force will continue the process of soliciting comments from various stakeholders, including the academic IS community and employers. The purpose of the AMCIS panel is to give the audience an update of the status of the MSIS 2016 revision process and provide the task force with feedback regarding the draft document. A significant portion of the session will be reserved for conversation. The task force is proposing significant changes to the curriculum …
Personalized And Adaptive Semantic Information Filtering For Social Media, Pavan Kapanipathi
Personalized And Adaptive Semantic Information Filtering For Social Media, Pavan Kapanipathi
Browse all Theses and Dissertations
Social media has experienced immense growth in recent times. These platforms are becoming increasingly common for information seeking and consumption, and as part of its growing popularity, information overload pose a significant challenge to users. For instance, Twitter alone generates around 500 million tweets per day and it is impractical for users to have to parse through such an enormous stream to find information that are interesting to them. This situation necessitates efficient personalized filtering mechanisms for users to consume relevant, interesting information from social media. Building a personalized filtering system involves understanding users' interests and utilizing these interests to …
Next Generation Of Product Search And Discovery, Kaiman Zeng
Next Generation Of Product Search And Discovery, Kaiman Zeng
FIU Electronic Theses and Dissertations
Online shopping has become an important part of people’s daily life with the rapid development of e-commerce. In some domains such as books, electronics, and CD/DVDs, online shopping has surpassed or even replaced the traditional shopping method. Compared with traditional retailing, e-commerce is information intensive. One of the key factors to succeed in e-business is how to facilitate the consumers’ approaches to discover a product. Conventionally a product search engine based on a keyword search or category browser is provided to help users find the product information they need. The general goal of a product search system is to enable …
Tascked: The Sanity Promoting Task Manager, Jake Tobin
Tascked: The Sanity Promoting Task Manager, Jake Tobin
Computer Science and Software Engineering
Personal task managers or various forms of to-do lists are abundant in our modern computing age. With the explosion of mobile computing technology, it is easier than ever to take notes digitally and make the data seemingly instantly available anywhere on the Internet. There is a fairly well defined core set of features in personal task managers available for public consumption, but it seems nothing that is publicly available provides feedback to the user or suggestions based on user history. Tascked is a task management solution, which records user history and solicits user feedback on progress. This allows the system …
A Personalized Hybrid Recommendation System Oriented To E-Commerce Mass Data In The Cloud, Fang Dong, Junzhou Luo, Xia Zhu, Yuxiang Wang, Jun Shen
A Personalized Hybrid Recommendation System Oriented To E-Commerce Mass Data In The Cloud, Fang Dong, Junzhou Luo, Xia Zhu, Yuxiang Wang, Jun Shen
Faculty of Engineering and Information Sciences - Papers: Part A
Personalized recommendation technology in Ecommerce is widespread to solve the problem of product information overload. However, with the further growth of the number of E-commerce users and products, the original recommendation algorithms and systems will face several new challenges: (1) to model user’s interests more accurately; (2) to provide more diverse recommendation modes; and (3) to support large-scale expansion. To address these challenges, from the actual demands of E-commerce applications (as Made-in-China website), a personalized hybrid recommendation system, which can support massive data set, is designed and implemented in this paper by using Cloud technology. Hereinto, the recommendation algorithms are …