10 must read research papers for crowd sourced mobile applications

Mobile and Crowdsourcing

10 must read research papers for crowdsourced mobile applicationsPresenter: Harshitha Chidananda

www 2015Early Detection of Spam Mobile AppsA method to detect spam apps solely using app

meta-data available at the time of publication.

(Adaptive Boost classifier)

www 2015A Novelty-Seeking based Dining Recommender SystemNDRS(novelty-seeking based dining recommender system)

Aim at generating the top-K restaurants for a user’s next dining by leveraging

• Users’ historical dining pattern

• Socio-demographic characteristics

• Restaurants attributes

Conditional Random Field (CRF) - Novelty

Hidden Markov Model (HMM) - Previously visited

ICWSM 2016Sentiment-Based Topic Suggestion for Micro-Reviewsnovel probabilistic models based on Latent Dirichlet Allocation (LDA) for

extracting the topics related to a user-venue pair.

Model integrates influences from both

• Venue inherent properties

• User preference

ICWSM 2015Predicting User Engagement on Twitter with Real-World Events

1)Operationalizing a person’s Twitter engagement in real-world events such as:

a) Posting

b) Retweeting

c) Replying to tweets about such events

2)Constructed statistical models that examine multiple predictive factors associated with users’ Twitter engagement

3)Quantify their potential influence on predicting

Ubicomp 2014User Interaction-based Profiling System for AndroidApplication TuningSystem provides meaningful analysis for application tuning from the provided fine-grained information:

• User interaction

• System behavior

• Power consumptionDoes not require source code of the application.

Uses web based framework

HotMobile 2015Mobile Touch-Free Interaction for Global HealthMaestro, a software-only gesture detection system that enables touch-free interaction on mobile devices.

Uses

• built-in, forward-facing camera

• computer vision

• Low power consumption

Ubicomp 2015SmartGPA: How Smartphones Can Assess and PredictAcademic Performance of College StudentsA simple model based on linear regression with lasso regularization that can accurately predict cumulative GPA. Uses:

• Time series analysis of activity

• Conversational interaction

• Mobility

• Class attendance

• Studying

• Partying

Ubicomp 2015Pick from Here! - An Interactive Mobile Cart using In-Situ Projection for Order PickingIntroduced a mobile camera-projector cart called OrderPickAR, which combines the benefits of both stationary and mobile systems to support order picking through Augmented Reality. The system dynamically projects in-situ picking information into the storage system and automatically detects when a picking task is done

Ubicomp 2015Activity Tracking:Barriers,Workarounds and Customisation

• Characterising the barriers users experienced• Reporting the workarounds they have created• Customizing based on workarounds

Mobisys 2015MAdScope: Characterizing Mobile In-App Targeted AdsA novel tool called MAdScope.

• Quickly harvest ads from a large collection of apps• Systematically probe an ad network to characterize its targeting

mechanism• Emulate user profiles of specific preferences and interests to study

behavioral targeting.

Thank You