Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization最新文献_第8页

FairUMAP 2019 Chairs' Welcome Overview 2019 FairUMAP主席欢迎概述

Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization Pub Date : 2019-06-06 DOI: 10.1145/3314183.3323842

Bettina Berendt, Veronika Bogina, R. Burke, Michael D. Ekstrand, Alan Hartman, S. Kleanthous, T. Kuflik, B. Mobasher, Jahna Otterbacher

{"title":"FairUMAP 2019 Chairs' Welcome Overview","authors":"Bettina Berendt, Veronika Bogina, R. Burke, Michael D. Ekstrand, Alan Hartman, S. Kleanthous, T. Kuflik, B. Mobasher, Jahna Otterbacher","doi":"10.1145/3314183.3323842","DOIUrl":"https://doi.org/10.1145/3314183.3323842","url":null,"abstract":"It is our great pleasure to welcome you to the Second FairUMAP workshop at UMAP 2019. This full-day workshop brings together researchers working at the intersection of user modeling, adaptation, and personalization on one hand, and bias, fairness and transparency in algorithmic systems on the other hand. The workshop was motivated by the observation that these two fields increasingly impact one another. Personalization has become a ubiquitous and essential part of systems that help users find relevant information in today's highly complex, information-rich online environments. Machine learning techniques applied to big data, as done by recommender systems, and user modeling in general, are key enabling technologies that allow intelligent systems to learn from users and adapt their output to users' needs and preferences. However, there has been a growing recognition that these underlying technologies raise novel ethical, legal, and policy challenges. It has become apparent that a single-minded focus on user characteristics has obscured other important and beneficial outcomes such systems must be able to deliver. System properties such as fairness, transparency, balance, and other social welfare considerations are not captured by typical metrics based on which data-driven personalized models are optimized. Indeed, widely-used personalization systems in popular sites such as Facebook, Google News and YouTube have been heavily criticized for personalizing information delivery too heavily at the cost of these other objectives.","PeriodicalId":240482,"journal":{"name":"Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133455735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Inferring Art Preferences from Gaze Exploration in a Museum 从博物馆的凝视探索推断艺术偏好

Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization Pub Date : 2019-06-06 DOI: 10.1145/3314183.3323871

Sylvain Castagnos, F. Marchal, Alexandre Bertrand, Morgane Colle, Djalila Mahmoudi

引用次数: 6

Privacy and Personalization: The Trade-off between Data Disclosure and Personalization Benefit 隐私与个性化:数据披露与个性化利益之间的权衡

Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization Pub Date : 2019-06-06 DOI: 10.1145/3314183.3323672

Lisa-Marie Wadle, Noemi Martin, Daniel Ziegler

引用次数: 8

The Impact of Social Connections in Personalization 社会关系对个性化的影响

Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization Pub Date : 2019-06-06 DOI: 10.1145/3314183.3323675

Carine Pierrette Mukamakuza, Dimitris Sacharidis, H. Werthner

引用次数: 2

Predicting Advertising Appeal from Receiver's Psychological Traits and Ad Design Features 从受众心理特征和广告设计特征预测广告吸引力

Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization Pub Date : 2019-06-06 DOI: 10.1145/3314183.3324979

Yuichi Ishikawa, Akihiro Kobayashi, A. Minamikawa

{"title":"Predicting Advertising Appeal from Receiver's Psychological Traits and Ad Design Features","authors":"Yuichi Ishikawa, Akihiro Kobayashi, A. Minamikawa","doi":"10.1145/3314183.3324979","DOIUrl":"https://doi.org/10.1145/3314183.3324979","url":null,"abstract":"This paper studies an approach for predicting an individual's perception of the advertising appeal of ad design. Although previous research has shown that people perceive an ad as more appealing when its design matches their psychological traits, the matching required the help of psychology experts, relying on their implicit knowledge. To exclude such dependence, we examined how the psychological traits affect perceived advertising appeal by conducting a questionnaire survey. Analyzing the survey results, we confirmed that psychological traits have significant moderating effects on both visual and linguistic features of an ad design in terms of how an individual perceives advertising appeal. We also confirmed that the moderating effects as well as main effects of visual and linguistic features have significant predictive utility for perceived appeal. The model in which the both effects are incorporated predicted the most appealing ad for each person more accurately than did a human without psychology expertise (accuracy lift: mean - 1.35, max - 2.48). While further study is necessary on whether the studied approach can serve as a substitute for psychology experts, we consider the present study took the first step toward realizing this goal.","PeriodicalId":240482,"journal":{"name":"Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115497267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Shaping the Reaction: Community Characteristics and Emotional Tone of Citizen Responses to Robotics Videos at TED versus YouTube 塑造反应:社区特征和公民对TED与YouTube机器人视频反应的情感基调

Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization Pub Date : 2019-06-06 DOI: 10.1145/3314183.3323673

S. Kleanthous, Jahna Otterbacher

引用次数: 0

Modeling Uncertainty in Group Recommendations 小组建议中的不确定性建模

Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization Pub Date : 2019-06-06 DOI: 10.1145/3314183.3324987

Dimitris Sacharidis

引用次数: 1

A Metacognitive Perspective of InfoVis in Education 教育信息信息的元认知视角

Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization Pub Date : 2019-06-06 DOI: 10.1145/3314183.3323674

Panagiotis Germanakos, Maria Kasinidou, Marios Constantinides, G. Samaras

引用次数: 1

UMAP 2019 Demo and Late-Breaking Results - Chairs' Preface UMAP 2019演示和最新成果-主席序言

Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization Pub Date : 2019-06-06 DOI: 10.1145/3314183.3324969

S. Kleanthous, M. Bieliková, B. Steichen

{"title":"UMAP 2019 Demo and Late-Breaking Results - Chairs' Preface","authors":"S. Kleanthous, M. Bieliková, B. Steichen","doi":"10.1145/3314183.3324969","DOIUrl":"https://doi.org/10.1145/3314183.3324969","url":null,"abstract":"It is our great pleasure to welcome you to the UMAP 2019 LBR and Demo Track, in conjunction with the 27th Conference on User Modelling, Adaptation and Personalization, held in Larnaca, Cyprus on June 9-12th, 2019. This track encompasses two categories: (i) Demos, which showcase research prototypes and commercially available products of UMAP-based systems, (ii) Late-breaking Results (LBR), which contain original and unpublished accounts of innovative research ideas, preliminary results, industry showcases, and system prototypes, addressing both the theory and practice of UMAP. The submissions spanned a wide scope of topics, ranging from novel techniques for user and group modeling, to adaptation and personalization implementations across different application scenarios. We received 46 LBR and 4 Demo submissions. Each submission was carefully reviewed by members of the Demo and LBR program committee, which consisted of 89 members. Each submission was reviewed by at least 3 PC members. Out of this total of 50 submissions, 15 LBR and 3 Demos were deemed of good quality by the reviewers, and were consequently accepted (36% overall acceptance rate). They were presented in the UMAP poster sessions, which collectively showcased the wide spectrum of novel ideas and latest results in user modelling, adaptation and personalization.","PeriodicalId":240482,"journal":{"name":"Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129488132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Museum Visitors Classification Based On Behavioral and Demographic Features 基于行为与人口特征的博物馆游客分类

Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization Pub Date : 2019-06-06 DOI: 10.1145/3314183.3323864

Moayad Mokatren, Veronika Bogina, A. Wecker, T. Kuflik

引用次数: 7