Related papers: Context Data Categories and Privacy Model for Mobi…
This paper formulates the problem of building a context-aware predictive model based on user diverse behavioral activities with smartphones. In the area of machine learning and data science, a tree-like model as that of decision tree is…
Organizations with a large user base, such as Samsung and Google, can potentially benefit from collecting and mining users' data. However, doing so raises privacy concerns, and risks accidental privacy breaches with serious consequences.…
Through lockdowns and other severe changes to daily life, almost everyone is affected by the COVID-19 pandemic. Scientists and medical doctors are - among others - mainly interested in researching, monitoring, and improving physical and…
The proliferation of smartphone devices has led to the emergence of powerful user services from enabling interactions with friends and business associates to mapping, finding nearby businesses and alerting users in real-time. Moreover,…
Privacy concerns have long been expressed around smart devices, and the concerns around Android apps have been studied by many past works. Over the past 10 years, we have crawled and scraped data for almost 1.9 million apps, and also stored…
People care more about the solutions to their problems rather than data alone. Inherently, this means using data to generate a list of recommendations for a given situation. The rapid growth of multi-modal wearables and sensors have not…
Smartphones enable understanding human behavior with activity recognition to support people's daily lives. Prior studies focused on using inertial sensors to detect simple activities (sitting, walking, running, etc.) and were mostly…
Understanding human mobility is essential for many fields, including transportation planning. Currently, surveys are the primary source for such analysis. However, in the recent past, many researchers have focused on Call Detail Records…
There are around a hundred installed apps on an average smartphone. The high number of apps and the limited number of app icons that can be displayed on the device's screen requires a new paradigm to address their visibility to the user. In…
As the distinction between personal and organizational device usage continues to blur, the combination of applications that interact increases the need to investigate potential security issues. Although security and forensic researchers…
Smartphones, equipped with an array of sensors, have become valuable tools for personal sensing. Particularly in digital health, smartphones facilitate the tracking of health-related behaviors and contexts, contributing significantly to…
Dating apps for mobile devices, one popular GeoSocial app category, are growing increasingly popular. These apps encourage the sharing of more personal information than conventional social media apps, including continuous location data.…
With the increased popularity of smartphones, various security threats and privacy leakages targeting them are discovered and investigated. In this work, we present \ourprotocoltight, a framework to authenticate users silently and…
In the age of data driven solution, the customer demographic attributes, such as gender and age, play a core role that may enable companies to enhance the offers of their services and target the right customer in the right time and place.…
Because of the growing interest for mobile device and pervasive applications deployed on cloud computing, the providing of intelligent and ubiquitous context-aware applications that take into account the user's context is one of the main…
Sensor data collected from smartphones provides the possibility to passively infer a user's personality traits. Such models can be used to enable technology personalization, while contributing to our substantive understanding of how human…
While the task of automatically detecting eating events has been examined in prior work using various wearable devices, the use of smartphones as standalone devices to infer eating events remains an open issue. This paper proposes a…
In today's digitized world, software systems must support users in understanding both how to interact with a system and why certain behaviors occur. This study investigates whether explanation needs, classified from user reviews, can be…
A context-aware recommender system (CARS) applies sensing and analysis of user context to provide personalized services. The contextual information can be driven from sensors in order to improve the accuracy of the recommendations. Yet,…
People living with dementia (PLwD) often show gradual shifts in how they communicate, becoming less expressive, more repetitive, or drifting off-topic in subtle ways. While caregivers may notice these changes informally, most computational…