User Perception of Situated Product Recommendations in Augmented Reality

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

Artificial Intelligence Review ◽

10.1007/s10462-021-10043-x ◽

2021 ◽

Author(s):

Shaina Raza ◽

Chen Ding

Keyword(s):

Recommender System ◽

Recent Progress ◽

System A ◽

Challenges And Opportunities

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CIRO: The Effects of Visually Diminished Real Objects on Human Perception in Handheld Augmented Reality

Electronics ◽

10.3390/electronics10080900 ◽

2021 ◽

Vol 10 (8) ◽

pp. 900

Author(s):

Hanseob Kim ◽

Taehyung Kim ◽

Myungho Lee ◽

Gerard Jounghyun Kim ◽

Jae-In Hwang

Keyword(s):

Augmented Reality ◽

Real World ◽

Human Perception ◽

Ground Truth ◽

Prior Work ◽

Comparative Experiment ◽

User Perception ◽

Depth Distortion ◽

Real Objects ◽

Visual Artifacts

Augmented reality (AR) scenes often inadvertently contain real world objects that are not relevant to the main AR content, such as arbitrary passersby on the street. We refer to these real-world objects as content-irrelevant real objects (CIROs). CIROs may distract users from focusing on the AR content and bring about perceptual issues (e.g., depth distortion or physicality conflict). In a prior work, we carried out a comparative experiment investigating the effects on user perception of the AR content by the degree of the visual diminishment of such a CIRO. Our findings revealed that the diminished representation had positive impacts on human perception, such as reducing the distraction and increasing the presence of the AR objects in the real environment. However, in that work, the ground truth test was staged with perfect and artifact-free diminishment. In this work, we applied an actual real-time object diminishment algorithm on the handheld AR platform, which cannot be completely artifact-free in practice, and evaluated its performance both objectively and subjectively. We found that the imperfect diminishment and visual artifacts can negatively affect the subjective user experience.

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Agricultural Loan Recommender System - A Machine Learning Approach

2021 International Conference on Innovative Trends in Information Technology (ICITIIT) ◽

10.1109/icitiit51526.2021.9399592 ◽

2021 ◽

Author(s):

Arsal Imtiaz ◽

S Nachiket ◽

K.V Nishanth ◽

Jyoti Angadi ◽

T.C Pramod

Keyword(s):

Machine Learning ◽

Recommender System ◽

Learning Approach ◽

System A ◽

Machine Learning Approach

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Public libraries digital services and sustainability issues

The Bottom Line Managing Library Finances ◽

10.1108/bl-12-2014-0034 ◽

2015 ◽

Vol 28 (1/2) ◽

pp. 34-43 ◽

Cited By ~ 5

Author(s):

Katarina Michnik

Keyword(s):

Public Libraries ◽

Qualitative Content Analysis ◽

Public Library ◽

Structured Interviews ◽

Content Type ◽

The Sustainable Development ◽

Digital Services ◽

Local Politicians ◽

Physical Spaces ◽

The Impact

Purpose – The purpose of this paper is to study how Swedish local politicians perceive the impact of public library digital services on public libraries and to discuss how this can affect the sustainable development of public libraries. Design/methodology/approach – Empirical data were collected through semi-structured interviews with local politicians from 19 different Swedish municipalities. Data were treated to qualitative content analysis and discussed based on the concept of sustainable organization. Findings – According to local politicians, public library digital services may affect public libraries through changes to libraries’ physical spaces, librarians’ tasks and competencies and libraries’ economic situations. Based on these findings, public library digital services can both strengthen and weaken public library sustainability through, for example, increased access and expenditures, the latter of which may threaten public library sustainability. Research limitations/implications – Interviews did not focus specifically on the politicians’ views on public library digital services but dealt generally with their views on public libraries. To identify reasons for variations in views on this topic, follow-up interviews should be done. Data on views from public library managers would also be of use to determine the degree to which they are shared with local politicians. Originality/value – When sustainability and public libraries are discussed, the focus is generally on the library’s contribution to a sustainable society. Here, the focus is instead on the sustainability of the public library itself.

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An Overview of the Recommender System

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.302.787 ◽

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.

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Adaptations in traditional courtyard houses in Baghdad, Iraq

International Journal of Building Pathology and Adaptation ◽

10.1108/ijbpa-03-2017-0013 ◽

2017 ◽

Vol 35 (4) ◽

pp. 348-363 ◽

Cited By ~ 3

Author(s):

Rand H.M. Agha ◽

John M. Kamara

Keyword(s):

Design Methodology ◽

Full Range ◽

Physical Structure ◽

Structured Interviews ◽

Content Type ◽

Case Study Analysis ◽

Physical Spaces ◽

Adaptation Model

Purpose The purpose of this paper is to investigate the adaptations that have been made to traditional courtyard houses (TCHs) in Baghdad, Iraq. The aim is to develop an understanding of various factors in the adaptation of these buildings to suit contemporary lifestyles, which will contribute to the wider field of building adaptability. Design/methodology/approach Empirical evidence was collected through case studies of 12 TCHs in the Al-Kadhimiya area of Baghdad, which involved a physical survey of buildings and semi-structured interviews with 24 occupants. Findings Case study analysis show that building adaptability involves both a change to physical spaces and also to lifestyles; with the latter being more likely when there are limitations in how much change can be made to the physical structure. Research limitations/implications The focus of this research is mainly on users’ adaptation of spaces and therefore does not consider the full range of stakeholders involved in the adaptation process. The findings also only apply to the cases considered and may not be applicable to other house types or locations. Originality/value Studies on building adaptability mostly focus on the ease of change to the building fabric, although the role of users is acknowledged. This study provides insights into the complexity and variety of changes that users can make, which are influenced by lifestyles and driven by the need for comfort. These insights are represented in an adaptation model, which can serve as a basis for further research.

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A Life-long Learning Recommender System to Promote Employability

International Journal of Emerging Technologies in Learning (iJET) ◽

10.3991/ijet.v12i06.7166 ◽

2017 ◽

Vol 12 (06) ◽

pp. 77 ◽

Cited By ~ 3

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.

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