scholarly journals News recommender system: a review of recent progress, challenges, and opportunities

2021 ◽  
Author(s):  
Shaina Raza ◽  
Chen Ding
Keyword(s):  
Recommender System ◽  
Recent Progress ◽  
System A ◽  
Challenges And Opportunities

scholarly journals The Combination of Building Greenery and Photovoltaic Energy Production—A Discussion of Challenges and Opportunities in Design

2021 ◽  
Vol 13 (3) ◽  
pp. 1537
Author(s):  
Irene Zluwa ◽  
Ulrike Pitha
Keyword(s):  
Energy Production ◽  
Substrate Surface ◽  
Relevant Literature ◽  
Green Roofs ◽  
Cooling Effect ◽  
Photovoltaic Energy ◽  
Pv Systems ◽  
System A ◽  
Challenges And Opportunities ◽  
Building Surfaces

In the case of building surfaces, the installation of green roofs or green facades can be used to reduce the temperature of the environment and the building. In addition, introducing photovoltaic energy production will help to reduce CO2 emissions. Both approaches (building greenery and photovoltaic energy production) compete, as both of them are located on the exterior of buildings. This paper aims to give an overview of solutions for the combination of building greenery (BG) systems and photovoltaic (PV) panels. Planning principles for different applications are outlined in a guideline for planning a sustainable surface on contemporary buildings. A comprehensive literature review was done. Identified solutions of combinations were systematically analysed and discussed in comparison with additional relevant literature. The main findings of this paper were: (A) BG and PV systems with low sub-construction heights require shallow substrates/low growing plants, whereas in the case of the combination of (a semi)-intensive GR system, a distance of a minimum 60 cm between the substrate surface and lower panel edge is recommended; (B) The cooling effect of the greenery depends on the distance between the PV and the air velocity; (C) if the substrate is dry, there is no evapotranspiration and therefore no cooling effect; (D) A spectrum of different PV systems, sub-constructions, and plants for the combination of BG and PV is necessary and suitable for different applications shown within the publication.

An Overview of the Recommender System

2013 ◽  
Vol 302 ◽  
pp. 787-791
Author(s):  
Lu Zhao ◽  
Rong Rong Yang ◽  
Meng Zhai ◽  
Feng Ming Liu
Keyword(s):  
Recommender System ◽  
System A ◽  
The Future

Delivering recommendation services are the trend of the future, so Recommender System varied very vital and widely applied in e-commerce websites to help customers in finding the items they want. A recommender system should be able to provide users with useful information about the items that might be interesting to them. The ability of immediately responding to changes in users preferences is a valuable asset for such systems. In recommender system, a variety of methods have been emerged as the basis for recommender. However, existing recommendation methods have the limitation. To overcome this limitation, we will propose new recommender system by combining the existing techniques. So, we firstly give an overview of recommender system for the future researches.

scholarly journals A Life-long Learning Recommender System to Promote Employability

2017 ◽  
Vol 12 (06) ◽  
pp. 77 ◽  
Author(s):  
David Baneres ◽  
Jordi Conesa
Keyword(s):  
Recommender System ◽  
Unemployed People ◽  
Knowledge And Skills ◽  
Professional Career ◽  
System A ◽  
Life Long Learning ◽  
University Courses ◽  
Job Offers ◽  
New Challenges

Is my professional knowledge outdated? Do I have the skills needed for the new challenges of the society? What knowledge do I lack to qualify for a job I like? What universities can I address to get knowledge that improves my employment expectations? These are relevant questions that all employees have done in any moment of their life. In addition, when there are high rates of unemployment and job offers that keep unfilled, the answers to these questions are even more relevant. Answering such questions open new opportunities for employed and unemployed people, by allowing them to design a formative plan according to their skills and expectations. It also provides evidences to employers about the skills and knowledge of the society, making them more aware of the skills of their potential future employees. The companies also will have more knowledge to design the professional career of their employees according to the company needs and the knowledge and skills of their employees. This paper proposes a system that helps people by showing which knowledge and skills a person misses for a given job position and what university courses the person can take to acquire the required skills and knowledge. The system has been implemented as a recommender system that helps users in planning their life-long learning. The paper shows the architecture of the proposed system, a case study to explain how it works, a survey to validate its usefulness and usability and some conclusions after its first experimentation.

scholarly journals Context-Aware Recommender System: A Review of Recent Developmental Process and Future Research Direction

2017 ◽  
Vol 7 (12) ◽  
pp. 1211 ◽  
Author(s):  
Khalid Haruna ◽  
Maizatul Akmar Ismail ◽  
Suhendroyono Suhendroyono ◽  
Damiasih Damiasih ◽  
Adi Pierewan ◽  
...  
Keyword(s):  
Recommender System ◽  
Developmental Process ◽  
Research Direction ◽  
Future Research ◽  
Context Aware ◽  
Future Research Direction ◽  
System A

IoT Recommender System: A Recommender System Based on Sensors from the Internet of Things for Points of Interest

2019 ◽  
pp. 237-250
Author(s):  
Cristian González García ◽  
Daniel Meana-Llorián ◽  
Vicente García Díaz ◽  
Edward Rolando Núñez-Valdez
Keyword(s):  
Internet Of Things ◽  
Recommender System ◽  
The Internet ◽  
System A ◽  
Points Of Interest ◽  
The Internet Of Things

scholarly journals An Adaptive Contextual Recommender System: a Slow Intelligence Perspective

2015 ◽  
Author(s):  
Francesco Colace ◽  
Luca Greco ◽  
Saverio Lemma ◽  
Marco Lombardi ◽  
Duncan Yung ◽  
...  
Keyword(s):  
Recommender System ◽  
System A

scholarly journals Stimuli Responsive, Programmable DNA Nanodevices for Biomedical Applications

2021 ◽  
Vol 9 ◽  
Author(s):  
Udisha Singh ◽  
Vinod Morya ◽  
Bhaskar Datta ◽  
Chinmay Ghoroi ◽  
Dhiraj Bhatia
Keyword(s):  
Biomedical Applications ◽  
Recent Progress ◽  
Dna Nanotechnology ◽  
Research Area ◽  
Biological Applications ◽  
Stimuli Responsive ◽  
Future Prospects ◽  
Dna Structures ◽  
Challenges And Opportunities

Of the multiple areas of applications of DNA nanotechnology, stimuli-responsive nanodevices have emerged as an elite branch of research owing to the advantages of molecular programmability of DNA structures and stimuli-responsiveness of motifs and DNA itself. These classes of devices present multiples areas to explore for basic and applied science using dynamic DNA nanotechnology. Herein, we take the stake in the recent progress of this fast-growing sub-area of DNA nanotechnology. We discuss different stimuli, motifs, scaffolds, and mechanisms of stimuli-responsive behaviours of DNA nanodevices with appropriate examples. Similarly, we present a multitude of biological applications that have been explored using DNA nanodevices, such as biosensing, in vivo pH-mapping, drug delivery, and therapy. We conclude by discussing the challenges and opportunities as well as future prospects of this emerging research area within DNA nanotechnology.

Collaborative-Based Movie Recommender System—A Proposed Model

2021 ◽  
pp. 561-571
Author(s):  
Prajna Paramita Parida ◽  
Mahendra Kumar Gourisaria ◽  
Manjusha Pandey ◽  
Siddharth Swarup Rautaray
Keyword(s):  
Recommender System ◽  
System A ◽  
Proposed Model

User Perception of Situated Product Recommendations in Augmented Reality

2019 ◽  
Vol 13 (03) ◽  
pp. 289-310
Author(s):  
Brandon Huynh ◽  
Adam Ibrahim ◽  
Yun Suk Chang ◽  
Tobias Höllerer ◽  
John O’Donovan
Keyword(s):  
Augmented Reality ◽  
Recommender System ◽  
Web Interface ◽  
User Perception ◽  
Structured Interviews ◽  
Physical Context ◽  
System A ◽  
Product Recommendations ◽  
Physical Spaces ◽  
Text Condition

Augmented reality (AR) interfaces increasingly utilize artificial intelligence systems to tailor content and experiences to the user. We explore the effects of one such system — a recommender system for online shopping — which allows customers to view personalized product recommendations in the physical spaces where they might be used. We describe results of a [Formula: see text] condition exploratory study in which recommendation quality was varied across three user interface types. Our results highlight potential differences in user perception of the recommended objects in an AR environment. Specifically, users rate product recommendations significantly higher in AR and in a 3D browser interface, and show a significant increase in trust in the recommender system, compared to a web interface with 2D product images. Through semi-structured interviews, we gather participant feedback which suggests AR interfaces perform better due to their ability to view products within the physical context where they will be used.

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