Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Collaborative filtering (3)
- E-commerce (3)
- Recommendation systems (3)
- Batteries (1)
- Battery charge measurement (1)
-
- Battery impedance estimation (1)
- Battery management system (1)
- Battery management systems (1)
- Clickstream data (1)
- Cloud interoperability (1)
- Computational modeling (1)
- Cross-federated cloud (1)
- Data models (1)
- Discharges (electric) (1)
- Electrical equivalent circuit models (1)
- Electrochemical impedance spectroscopy (EIS) (1)
- Federated cloud (1)
- Historical purchases (1)
- Hybrid federated cloud (1)
- Inter-cloud (1)
- Li-ion batteries (1)
- Li-ion battery (LIB) (1)
- Markov model (1)
- Multi-cloud (1)
- OCV characterization (1)
- OCV modeling (1)
- OCV-SOC characterization (1)
- OCV-SOC modeling (1)
- Privacy (1)
- Purchase and click stream (1)
Articles 1 - 6 of 6
Full-Text Articles in Entire DC Network
A Survey And Taxonomy Of Sequential Recommender Systems For E-Commerce Product Recommendation, Mahreen Nasir, C. I. Ezeife
A Survey And Taxonomy Of Sequential Recommender Systems For E-Commerce Product Recommendation, Mahreen Nasir, C. I. Ezeife
Computer Science Publications
E-commerce recommendation systems facilitate customers’ purchase decision by recommending products or services of interest (e.g., Amazon). Designing a recommender system tailored toward an individual customer’s need is crucial for retailers to increase revenue and retain customers’ loyalty. As users’ interests and preferences change with time, the time stamp of a user interaction (click, view or purchase event) is an important characteristic to learn sequential patterns from these user interactions and, hence, understand users’ long- and short-term preferences to predict the next item(s) for recommendation. This paper presents a taxonomy of sequential recommendation systems (SRecSys) with a focus on e-commerce product …
A Survey Of Sequential Pattern Based E-Commerce Recommendation Systems, Christie I. Ezeife, Hemni Karlapalepu
A Survey Of Sequential Pattern Based E-Commerce Recommendation Systems, Christie I. Ezeife, Hemni Karlapalepu
Computer Science Publications
E-commerce recommendation systems usually deal with massive customer sequential databases, such as historical purchase or click stream sequences. Recommendation systems’ accuracy can be improved if complex sequential patterns of user purchase behavior are learned by integrating sequential patterns of customer clicks and/or purchases into the user–item rating matrix input of collaborative filtering. This review focuses on algorithms of existing E-commerce recommendation systems that are sequential pattern-based. It provides a comprehensive and comparative performance analysis of these systems, exposing their methodologies, achievements, limitations, and potential for solving more important problems in this domain. The review shows that integrating sequential pattern mining …
Battery Parameter Analysis Through Electrochemical Impedance Spectroscopy At Different State Of Charge Levels, Yuchao Wu, Sneha Sundaresan, Balakumar Balasingam
Battery Parameter Analysis Through Electrochemical Impedance Spectroscopy At Different State Of Charge Levels, Yuchao Wu, Sneha Sundaresan, Balakumar Balasingam
Computer Science Publications
This paper presents a systematic approach to extract electrical equivalent circuit model (ECM) parameters of the Li-ion battery (LIB) based on electrochemical impedance spectroscopy (EIS). Particularly, the proposed approach is suitable to practical applications where the measurement noise can be significant, resulting in a low signal-to-noise ratio. Given the EIS measurements, the proposed approach can be used to obtain the ECM parameters of a battery. Then, a time domain approach is employed to validate the accuracy of estimated ECM parameters. In order to investigate whether the ECM parameters vary as the battery’s state of charge (SOC) changes, the EIS experiment …
Semantic Enhanced Markov Model For Sequential E-Commerce Product Recommendation, Mahreen Nasir, C. I. Ezeife
Semantic Enhanced Markov Model For Sequential E-Commerce Product Recommendation, Mahreen Nasir, C. I. Ezeife
Computer Science Publications
To model sequential relationships between items, Markov Models build a transition probability matrix P of size n× n, where n represents number of states (items) and each matrix entry p(i,j) represents transition probabilities from state i to state j. Existing systems such as factorized personalized Markov chains (FPMC) and fossil either combine sequential information with user preference information or add the high-order Markov chains concept. However, they suffer from (i) model complexity: an increase in Markov Model’s order (number of states) and separation of sequential pattern and user preference matrices, (ii) sparse transition probability matrix: few product purchases from thousands …
Survey Of Multiple Clouds: Classification, Relationships And Privacy Concerns, Reem Al-Saidi, Ziad. Kobti
Survey Of Multiple Clouds: Classification, Relationships And Privacy Concerns, Reem Al-Saidi, Ziad. Kobti
Computer Science Publications
When major Cloud Service Providers (CSPs) network with other CSPs, they show a predominant area over cloud computing architecture, each with different roles to serve user demands better. This creates multiple clouds computing environments, which overcome the limitations of cloud computing and bring a wide range of benefits (e.g., avoiding vendor lock-in problem). Numerous applications can use various multiple clouds types depending on their specifications and needs. Deploying multiple clouds under hybrid or public models has introduced various privacy concerns that affect users and their data in a specific application domain. To understand the nuances of these concerns, the present …
Performance Analysis Of Empirical Open-Circuit Voltage Modeling In Lithium-Ion Batteries, Part-3: Experimental Results, Prarthana Pillai, James Nguyen, Balakumar Balasingam
Performance Analysis Of Empirical Open-Circuit Voltage Modeling In Lithium-Ion Batteries, Part-3: Experimental Results, Prarthana Pillai, James Nguyen, Balakumar Balasingam
Computer Science Publications
This paper is the third part of a series of papers about empirical approaches to open circuit voltage (OCV) modeling of lithium-ion batteries. The first part of the series proposed models to quantify various sources of uncertainties in the OCV models; the second part of the series presented systematic data collection approaches to compute the uncertainties in the OCV to state of charge (SOC) models. This paper uses data collected from 28 OCV characterization experiments, performed according to the data collection plan presented in the second part, to compute and analyze three OCV uncertainty metrics: cell-to-cell variations, C-Rate error, and …