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Incremental Learning with Accuracy Prediction of Social and Individual Properties from Mobile-Phone Data
2012
2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing
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A great deal of research effort in academia and industry is put into mining this raw data for higher level sense-making, such as understanding user context, inferring social networks, learning individual ...
As truly ubiquitous wearable computers, mobile phones are quickly becoming the primary source for social, behavioral, and environmental sensing and data collection. ...
Specifically, we investigate the learning and prediction of social and individual models from raw phone-sensed data. ...
doi:10.1109/socialcom-passat.2012.102
dblp:conf/socialcom/AltshulerAFEP12
fatcat:kbgv6mhdmnax5i7i6hwux6jepm
How Many Makes a Crowd? On the Evolution of Learning as a Factor of Community Coverage
[chapter]
2012
Lecture Notes in Computer Science
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In particular, we examine how the ability to predict individual features and social links is incrementally enhanced with the accumulation of additional data. ...
In this work we investigate the properties of learning and inferences of real world data collected via mobile phones for different sizes of analyzed networks. ...
We demonstrate the characteristics of incremental learning of multiple social and individual properties from raw sensing data collected from mobile phones while the information is accumulated from a multitude ...
doi:10.1007/978-3-642-29047-3_6
fatcat:efuwbsmfpfckfl6qrlzcpi2d6u
Effectiveness analysis of machine learning classification models for predicting personalized context-aware smartphone usage
2019
Journal of Big Data
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The effectiveness of these classifier based context-aware models is examined by conducting a range of experiments on the real mobile phone datasets collected from individual users. ...
Recently, with the rapid advances in context-aware mobile technologies and increasing popularity of data science research, data-driven personalized mobile services and systems are emerging as an important ...
In the area of mining mobile phone data, classification is the most popular machine learning technique to model and predict individual's such activities with their phones. ...
doi:10.1186/s40537-019-0219-y
fatcat:ixrbu7qp2rcp5g4gaflyzh3zfi
RecencyMiner: mining recency-based personalized behavior from contextual smartphone data
2019
Journal of Big Data
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An individual smartphone's ability to store user's such diverse activities and associated contexts with their phones enables the study on data-driven smartphone usage behavior modeling and prediction [ ...
Due to the recent advanced features in smartphones and the popularity of context-awareness in mobile technologies, individual's behavioral activities with their phones, such as phone call activities, mobile ...
Acknowledgements The authors would like to thank the administrative staff of Swinburne University of Technology, Melbourne, Australia, for their support while doing this work and experiment in their post-graduate ...
doi:10.1186/s40537-019-0211-6
fatcat:dqbhlaesjbbdxaub5k5vwm7c6m
Predicting financial trouble using call data—On social capital, phone logs, and financial trouble
2018
PLoS ONE
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This work reports results from one of the largest known studies connecting financial outcomes and phone-based social behavior (180,000 individuals; 2 years' time frame; 82.2 million monthly bills, and ...
An ability to understand and predict financial wellbeing for individuals is of interest to economists, policy designers, financial institutions, and the individuals themselves. ...
Acknowledgments The authors are indebted to the officials of the bank and telecommunications operator, which has chosen to remain anonymous, for making the transaction dataset and call dataset available ...
doi:10.1371/journal.pone.0191863
pmid:29474411
pmcid:PMC5825009
fatcat:wqp4vluperbnfkz7m6uasrv6vq
An Analysis of Location Prediction Models
2020
International Journal of Computer Applications
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This paper places emphasizes on the relevance of location prediction models in mobile users. ...
Although this article does not give an exhaustive survey of all techniques and applications but it gives a description of several types of algorithms and models used for location prediction. ...
CONCLUSION This research has analyzed various location prediction models, their objectives and also stated their various limitations. ...
doi:10.5120/ijca2020920063
fatcat:lstc4uzdrbg3pegwzd2ftnrfsy
Mobile big data analysis with machine learning
[article]
2020
arXiv
pre-print
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This paper investigates to identify the requirement and the development of machine learning-based mobile big data analysis through discussing the insights of challenges in the mobile big data (MBD). ...
Finally, we summarize the main challenges and future development directions of mobile big data analysis. ...
from the view of mobile traffic data Figure 8 . and depict offline and online social network separately. ...
arXiv:1808.00803v2
fatcat:42l62ikc2rhd3bzuao25hhrwgm
Survey of wireless big data
2017
Journal of Communications and Information Networks
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While these data share some common properties with traditional big data, they have their own unique characteristics and provide numerous advantages for academic research and practical applications. ...
Wireless big data describes a wide range of massive data that is generated, collected and stored in wireless networks by wireless devices and users. ...
[38] analyzed the travel patterns in the mobile phone call data records of 500 000 individuals and verified that the theoretical maximum predictability is as high as 88%. ...
doi:10.1007/s41650-017-0001-2
fatcat:62r2dkm4inesrg3j3r3f3obgxm
Human mobility in opportunistic networks: Characteristics, models and prediction methods
2014
Journal of Network and Computer Applications
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Firstly, spatial, temporal, and connectivity properties of human motion are explored. ...
Opportunistic networks (OppNets) are modern types of intermittently connected networks in which mobile users communicate with each other via their short-range devices to share data among interested observers ...
Acknowledgments This research is sponsored in part by the National Natural Science Foundation of China (Contract/Grant Nos. 61173179 and 61202441). ...
doi:10.1016/j.jnca.2014.03.007
fatcat:uoq7l77p6vfl3oq2o45t5hwjmq
Preference, context and communities
2013
Proceedings of the 17th annual international symposium on International symposium on wearable computers - ISWC '13
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Reliable smartphone app prediction can strongly benefit both users and phone system performance alike. ...
We evaluate a multi-faceted approach to prediction using (1) a 3-week 35-user field trial, along with (2) analysis of app usage logs of 4,606 smartphone users worldwide. ...
Segment Sensor/Phone Data into App Bags Our framework begins by gathering traces of training data from smartphone users that contain (1) sensor and phone state data and (2) a log of smartphone app usage ...
doi:10.1145/2493988.2494333
dblp:conf/iswc/XuLLCLCCC13
fatcat:brwgn7yvirh5dgnqfmlh3sjpu4
Naive Bayes Algorithm Mining Mobile Phone Trojan Crime Clues
2022
Mobile Information Systems
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And based on the feature set data extracted from the network data packets, it conducts an in-depth analysis of the current business behaviors of mobile phone Trojans, such as propagation and implantation ...
With this trend, the importance of mobile phone information security is also increasing day by day. How to prevent mobile phone virus has gradually become an important issue. ...
data, and so on, to commit crimes of infringement of property and disrupting the order of social management. even crimes that endanger national security. e popularity of smart phones has brought a new ...
doi:10.1155/2022/6262147
fatcat:taycwovievho5j5hqvgyvqiyhi
Finding your friends and following them to where you are
2012
Proceedings of the fifth ACM international conference on Web search and data mining - WSDM '12
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We evaluate Flap on a large sample of highly active users from two distinct geographical areas and show that it (1) reconstructs the entire friendship graph with high accuracy even when no edges are given ...
For location prediction, Flap implements a scalable probabilistic model of human mobility, where we treat users with known GPS positions as noisy sensors of the location of their friends. ...
granularity; and learns the candidate locations from noisy data. ...
doi:10.1145/2124295.2124380
dblp:conf/wsdm/SadilekKB12
fatcat:ha6goxl3bvanjbsc7qvfzwwfeu
Recognizing Context-Aware Human Sociability Patterns Using Pervasive Monitoring for Supporting Mental Health Professionals
2020
Sensors
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Evaluation results show that the prediction performance of the identified context-aware sociability patterns has strong positive relation (Pearson's correlation coefficient >70%) with individuals' social ...
As an alternative, we present a solution to detect context-aware sociability patterns and behavioral changes based on social situations inferred from ubiquitous device data. ...
on context data derived from mobile, wearable, and Internet of Things (IoT) computing devices [13] . ...
doi:10.3390/s21010086
pmid:33375630
fatcat:ruyavlolwfbg7aoslunazpseou
Complex Systems and a Computational Social Science Perspective on the Labor Market
[article]
2016
arXiv
pre-print
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In particular, we explore the benefits of leveraging tools from computational social science, network science, and data-driven theories to measure the flow of opportunities and information in the context ...
At the individual level, unemployment often has a detrimental impact on people's well-being and health. ...
We examined anonymized mobile phone metadata combined with beneficiaries' records from an unemployment benefit program, and found that aggregated activity, social, and mobility patterns strongly correlate ...
arXiv:1606.08562v1
fatcat:vr4ncqc5lzeazm3uxsbaclcsm4
Mobile Homophily and Social Location Prediction
[article]
2015
arXiv
pre-print
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Using a large LBSN dataset, his paper investigates the interdependency between human mobility and social proximity, the influence of social networks on enhancing location prediction of an individual and ...
a lot and are explorative by nature, which may hamper the prediction of their mobility. ...
Using a large mobile phone based data-set with cell-tower-based localization granularity, [78] also investigate social ties and social tie strength in relation to the mobility patterns of the respective ...
arXiv:1506.07763v1
fatcat:eikc3cfvgbg7fi4a24mwncxwzu
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