The Workshop on Mining and Learning from Smartphones Apps for Users
In conjunction with the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2019)
Date and Location: Sept. 10th (Day 2), Afternoon, Room Abbey, QEII Centre in London, UK
Smartphone applications (abbr. apps) are ubiquitous in our daily life. Abundant apps provide useful services in almost every aspect of modern life. Easy to download and often free, apps can be fun and convenient for playing games, getting turn-by-turn directions, and accessing news, books, weather, and more. Apps on smartphones can be considered as the entry point to access everyday life services such as communication, shopping, navigation, and entertainment. Since a smartphone is linked to an individual user, apps in smartphones can sense users’ behavior and activities.
Researchers can use smartphone apps to record users’ personal history data, and use the data to analyze apps and understand users. In this workshop (AppLens 2019), we bring researchers together with an interest in understanding users from their use of smartphone apps (e.g., interests, personality, and life routines), discovering cultural and social phenomenon (e.g., social event detection) through analyzing app usage, recognizing app usage behaviors (e.g., app overuse detection), studying smartphone apps (e.g., app categorization and app popularity prediction), and user privacy issues. We want researchers to share their experiences, success and frustrations on conducting research in such topics so as to capture a state-of-art on theories, models, and methodologies that cope with these challenges.
We are opening two app datasets to look for novel contributions in this research field. This workshop will include paper sessions and invited talks. Moreover, we will select a few accepted papers to be extended and published in a prestigious journal special issue.
We are opening two app datasets on AppLens 2019. The submissions are not limited to the ones based on the provided datasets. The researchers can also make submissions based on other app related datasets.The dataset does not contain any personally identifying information. If you have any question about the datasets, please feel free to contact Yong Li (liyong07 AT Tsinghua.edu.cn). The datasets include:
The workshop fosters discussions covering methodologies and tools, theories and models, design, or descriptions in the topics such as (but not limited to):
The goal of the workshop is to gather a community that focuses on mining and learning from smartphone apps for users. We provide a platform for participants both in academia and industry that are interested in the topics.
(The template changes) We welcome both of regular (up to 8 pages) and short (up to 4 pages) paper contributions submitted as PDF files. We also encourage submissions of work-in-progress papers.
The template can be downloaded here: https://www.acm.org/publications/proceedings-template. Alternatively, the Overleaf version can be found here: https://www.overleaf.com/latex/templates/acm-conference-proceedings-master-template/pnrfvrrdbfwt. Latex documents should use the "sigchi" template style. Word users should use the interim template downloadable from the the ACM link above.
(The template changes) Submissions can be made at https://new.precisionconference.com/sigchi. (On the submissions tab, select SIGCHI society and UbiComp 2019 conference. Then the submission track of UbiComp 2019 Workshop - AppLens will appear.)
All submitted papers will be reviewed and judged on originality, technical correctness, relevance, and quality of presentation by the Program Committee. All accepted submissions must be presented during the workshop. Papers will be given a total of 25 minutes including questions (we suggest you reserve 3-5 minutes for questions).
The accepted papers will be published in the UbiComp 2019/ISWC Adjunct Proceedings, which will be included in the ACM Digital Library. The extended versions of selected workshop papers will be published in a journal special issue after the workshop.
If you have any question, please feel free to contact firstname.lastname@example.org.
Sha Zhao is a Postdoctoral Research Fellow with the College of Computer Science and Technology, Zhejiang University. Contact her at email@example.com
Yong Li is a Associate Professor with the Department of Electronic Engineering, Tsinghua University. Contact him at firstname.lastname@example.org
Sasu Tarkoma is a Professor and Head the Department of Computer Science at the University of Helsinki. Contact him at email@example.com
Zhiwen Yu is a Professor and vice dean in the School of Computer Science, Northwestern Polytechnical University. Contact him at firstname.lastname@example.org
Anind Dey is a Professor and Dean of the Information School, University of Washington. Contact him at email@example.com
Gang Pan is a Professor with the College of Computer Science and Technology, Zhejiang University. Contact him at firstname.lastname@example.org
Organizers: Yong Li (Tsinghua University, China), Vassilis Kostakos (University of Melbourne, Australia), Sha Zhao (Zhejiang University, Hangzhou, China), Sasu Tarkoma (University of Helsinki, Finland)
09:00-09:45 Background, App Data Collection and Datasets (Sasu Tarkoma, Yong Li)
09:45-10:30 Smartphone App Usage Modeling (Vassilis Kostakos)
10:45-11:30 App Usage Prediction and Recommendation(Yong Li)
11:30-12:15 User Profiling from the App Usage (Sha Zhao)
All accepted submissions must be presented during the workshop.
Papers will be given a total of 25 minutes including questions (we suggest you reserve 3-5 minutes for questions).
Note: The room has a 16:9 projector with full-size HDMI connector.
Title: Sensing Nightlife
Speaker: Professor Daniel Gatica-Perez, idiap research institute, Switzerland
Prof. Daniel Gatica-Perez directs the Social Computing Group at Idiap and EPFL in Switzerland. His research integrates theories and methods from ubiquitous computing, social media, machine learning, and social sciences to understand human and social behavior in everyday life for social good applications. His current work includes mobile crowdsensing in cities and large-scale analysis of social media, smartphone data, and open data. His research has been supported by the Swiss National Science Foundation, the Swiss Commission for Technology and Innovation, the European Commission, and several industry partners. He also works with cities and local organizations on social innovation projects.
Abstract: The behavior and practices of youth in the context of nightlife are subjects of study in different disciplines, spanning urban crowdsourcing and social media analytics in ubicomp and social computing; youth culture in human geography; and environmental factors of alcohol use in public health. I will present an overview of our research in this domain, and talk about computational methods for characterization of nightlife places and activities from crowdsourced videos; analysis of drinking-related practices in social media posts; and recognition of alcohol consumption patterns from smartphone sensors. I will conclude by discussing future directions for multidisciplinary ubicomp research.
14:15-14:40 Invited Paper: Deep Learning on Smartphone apps
Speaker: Dr. Yun Ma Peking University
14:40-15:05 Discovering Eating Routines in Context with a Smartphone App
Daniel Gatica-Perez, Joan-Isaac Biel, David Labbe, Nathalie Martin
15:05-15:30 Activity Recognition in Outdoor Sports Environments: Smart Data for End-Users Involving Mobile Pervasive Augmented Reality Systems
Rui Pascoal, Ana de Almeida, Rute C. Sofia
16:00-16:25 Invited Paper: Context-aware App Usage Prediction
Speaker: Fengli Xu Tsinghua University
16:25-16:50 Smartphone Interaction and Survey Data as Predictors of Snapchat Usage
Beryl Noë, Liam D. Turner, Roger M. Whitaker.
16:50-17:15 A Novel Smartphone Application for Indoor Positioning of Users based on Machine Learning
Mohammad Nabati, Reza Shahbazian, Elaheh Homayounvala, Seyed Ali Ghorashi