scholarly journals Airport Restroom Cleanliness Prediction Using Real Time User Feedback Data

Author(s):  
Kilian Ros ◽  
Elena Mocanu ◽  
Christin Seifert
Author(s):  
David Monaghan ◽  
Freddie Honohan ◽  
Amin Ahmadi ◽  
Troy McDaniel ◽  
Ramin Tadayon ◽  
...  

Author(s):  
William Albert Young II ◽  
Brett H. Hicks ◽  
Danielle Villa-Lobos ◽  
Teresa J. Franklin

This paper explores the use of Professor-Developed Multimedia Content (PDMC) in online, distance education to build a community of inquiry (CoI) through enhanced social presence and real-time, student-driven, adaption of the learning content. The foundation of higher education has long been, developing curriculum to meet educational objectives. Most often faculty relies on assessment information gained at the end of each course. Then assessments, formative and summative, are re-designed based on student feedback/data from end of course surveys and educational materials such as textbooks, articles, and test banks are updated with newer editions. In the distance-learning environment, PDMC provides a creative, innovative, and interactive ways to engage the student for real-time learning. Still, the ability to target PDMC materials to the correct sub-sections of our classroom cohort can produce a richer, more immerse learning experience and perhaps become the closet recreation of in-seat, traditional classroom learning in a distance/online environment. By using PDMC with corresponding surveys, educators can obtain real-time data and metrics to alter content in the classroom immediately, and develop media content welcoming sub-sets of learners with desired content based on learning needs, desires, and feedback.


2013 ◽  
Vol 38 (1) ◽  
pp. 67-83 ◽  
Author(s):  
Andrzej Szwabe ◽  
Pawel Misiorek ◽  
Michal Ciesielczyk ◽  
Czeslaw Jedrzejek

Abstract Widely-referenced approaches to collaborative filtering (CF) are based on the use of an input matrix that represents each user profile as a vector in a space of items and each item as a vector in a space of users. When the behavioral input data have the form of (userX, likes, itemY) and (userX, dislikes, itemY) triples one has to propose a representation of the user feedback data that is more suitable for the use of propositional data than the ordinary user-item ratings matrix. We propose to use an element-fact matrix, in which columns represent RDF-like behavioral data triples and rows represent users, items, and relations. By following such a triple-based approach to the bi-relational behavioral data representation we are able to improve the quality of collaborative filtering. One of the key findings of the research presented in this paper is that the proposed bi-relational behavioral data representation, while combined with reflective matrix processing, significantly outperforms state-of-the-art collaborative filtering methods based on the use of a ‘standard’ user-item matrix.


2021 ◽  
Author(s):  
Zerina Lokmic-Tomkins ◽  
Philippa Marriott ◽  
Annie Tuddenham ◽  
Joanne Martin

During COVID-19 pandemic public health measures, face-to-face simulation laboratories were cancelled. A rapid transition to online teaching environments required staff and students to rapid upskilling in digital literacy. The purpose of this article is to describe a model of virtual nursing simulation laboratory implemented in graduate entry to practice Master’s nursing program to teach clinical skills. The model used cloud-based communication app Zoom and real time feedback data to improve content delivery, student engagement and confidence in skill development. This model was co-designed with the student cohort to ensure students, as stakeholders, had a voice in having their education needs met during these challenging times.


2018 ◽  
Vol 7 (2.7) ◽  
pp. 51
Author(s):  
T V.R. Sai ◽  
SK Haaris ◽  
S Sridevi

In this project we used opinion mining methods to evaluate various websites present on the internet. We also analyzed the approaches, tools, and dataset used by Scholars with their accuracy and we used this technology for evaluation of a website. Opinion mining is used in various scenarios around the world. But it is hardly used in websites evaluation which we are implementing with this project, as now a day’s, websites we regularly use are spamming with advertisements and unusable content. This paper proposed a frame work of evaluating a website using the user feedback on the website collected on our website. That collected feedback data is processed using a data mining software that is rapid miner. 


2013 ◽  
Vol 756-759 ◽  
pp. 833-836
Author(s):  
Tian Chong ◽  
Yan Ling Shao ◽  
Jian Jun Wang

This paper presents a model based on analysis on interactive users search needs. This model changes from the analysis on user's behavior to the one on search content, which reduces to violate users privacy, and enables users to actively participate in determining the needs of search from the client end in the search engine, in addition to establishment of search demand model based on a large number of user feedback data mining in the search engine subsystem, as a result of higher search precision with less client spending and higher user s participation.


2011 ◽  
pp. 147-166 ◽  
Author(s):  
Babis Magoutas

This chapter introduces a semantically adaptive interface as a means of measuring the quality of egovernment portals, based on user feedback. The interface is semantic as it uses ontologies in order to formalize well defined semantics about the adaptation criteria used. Furthermore it is adaptive as three axes of adaptation are applied: based on real-time feedback from users, based on problems encountered by the user and based on metadata of the pages visited by the user. The authors hope that applying the proposed adaptive interface as a means of measuring e-government portals’ quality, will not only allow more focused and targeted assessment of quality, but will also increase users’ response rates.


2018 ◽  
Vol 39 (1) ◽  
pp. 014005 ◽  
Author(s):  
Thomas De Cooman ◽  
Troels W Kjær ◽  
Sabine Van Huffel ◽  
Helge B Sorensen

Sign in / Sign up

Export Citation Format

Share Document