2021 IEEE/ACM 8th International Conference on Mobile Software Engineering and Systems (MobileSoft)最新文献_第2页

MeetDurian: A Gameful Mobile App to Prevent COVID-19 Infection MeetDurian:一个有趣的手机应用程序，以防止COVID-19感染

2021 IEEE/ACM 8th International Conference on Mobile Software Engineering and Systems (MobileSoft) Pub Date : 2021-04-01 DOI: 10.1109/MobileSoft52590.2021.00016

Dongliang Chen, A. Bucchiarone, Zhihan Lv

引用次数: 2

Developing Apps for Researching the COVID-19 Pandemic with the TrackYourHealth Platform 使用TrackYourHealth平台开发用于研究COVID-19大流行的应用程序

2021 IEEE/ACM 8th International Conference on Mobile Software Engineering and Systems (MobileSoft) Pub Date : 2021-03-25 DOI: 10.1109/MobileSoft52590.2021.00015

Carsten Vogel, R. Pryss, Johannes Schobel, W. Schlee, Felix Beierle

引用次数: 9

Assessing the Feasibility of Web-Request Prediction Models on Mobile Platforms 移动平台上web请求预测模型的可行性评估

2021 IEEE/ACM 8th International Conference on Mobile Software Engineering and Systems (MobileSoft) Pub Date : 2020-11-10 DOI: 10.1109/MobileSoft52590.2021.00008

Yixue Zhao, Siwei Yin, Adriana Sejfia, Marcelo Schmitt Laser, Haoyu Wang, N. Medvidović

{"title":"Assessing the Feasibility of Web-Request Prediction Models on Mobile Platforms","authors":"Yixue Zhao, Siwei Yin, Adriana Sejfia, Marcelo Schmitt Laser, Haoyu Wang, N. Medvidović","doi":"10.1109/MobileSoft52590.2021.00008","DOIUrl":"https://doi.org/10.1109/MobileSoft52590.2021.00008","url":null,"abstract":"Prefetching web pages is a well-studied solution to reduce network latency by predicting users’ future actions based on their past behaviors. However, such techniques are largely unexplored on mobile platforms. Today’s privacy regulations make it infeasible to explore prefetching with the usual strategy of amassing large amounts of data over long periods and constructing conventional, \"large\" prediction models. Our work is based on the observation that this may not be necessary: Given previously reported mobile-device usage trends (e.g., repetitive behaviors in brief bursts), we hypothesized that prefetching should work effectively with \"small\" models trained on mobile-user requests collected during much shorter time periods. To test this hypothesis, we constructed a framework for automatically assessing prediction models, and used it to conduct an extensive empirical study based on over 15 million HTTP requests collected from nearly 11,500 mobile users during a 24-hour period, resulting in over 7 million models. Our results demonstrate the feasibility of prefetching with small models on mobile platforms, directly motivating future work in this area. We further introduce several strategies for improving prediction models while reducing the model size. Finally, our framework provides the foundation for future explorations of effective prediction models across a range of usage scenarios.","PeriodicalId":257528,"journal":{"name":"2021 IEEE/ACM 8th International Conference on Mobile Software Engineering and Systems (MobileSoft)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133283278","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

Title Page iii 第三页标题

2021 IEEE/ACM 8th International Conference on Mobile Software Engineering and Systems (MobileSoft) Pub Date : 2018-06-01 DOI: 10.1109/focs.2018.00002

Los Alamitos, C. Washington, bullet Tokyo

引用次数: 0

[Copyright notice] (版权)

2021 IEEE/ACM 8th International Conference on Mobile Software Engineering and Systems (MobileSoft) Pub Date : 1900-01-01 DOI: 10.1109/mobilesoft52590.2021.00003

引用次数: 0