Location-Based Advertising Using Location-Aware Data Mining

2018 ◽  
pp. 196-211
Author(s):  
Wen-Chen Hu ◽  
Naima Kaabouch ◽  
Hongyu Guo ◽  
AbdElRahman Ahmed ElSaid
Keyword(s):  
Data Mining ◽  
Mobile Devices ◽  
Farmers Markets ◽  
Mobile Users ◽  
Location Information ◽  
Grocery Stores ◽  
User Privacy ◽  
Location Aware ◽  
To Receive

This chapter describes how mobile advertisements are critical for both mobile users and businesses as people spend more time on mobile devices than on PCs. However, how to send relevant advertisements and avoid unnecessary ones to specific mobile users is always a challenge. For example, a concert-goer may like to visit restaurants or parks before the concert and may not like the advertisements of grocery stores or farmers' markets. This research tries to overcome the challenge by using the methods of location-aware data mining. Furthermore, privacy is always a great concern for location-based advertising (LBA) users because their location information has to be shared in order to receive the services. This chapter also takes the concern into serious consideration, so the user privacy will not be compromised. Preliminary experiment results show the proposed methods are effective and user-privacy is rigorously preserved.

scholarly journals How Dangerous Are Your Smartphones? App Usage Recommendation with Privacy Preserving

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Konglin Zhu ◽  
Xiaoman He ◽  
Bin Xiang ◽  
Lin Zhang ◽  
Achille Pattavina
Keyword(s):  
Mobile Devices ◽  
Mobile Apps ◽  
Critical Issue ◽  
Mobile App ◽  
User Preference ◽  
Mobile Users ◽  
User Privacy ◽  
The Past ◽  
Privacy Leakage ◽  
Privacy Violation

With the rapid proliferation of mobile devices, explosive mobile applications (apps) are developed in the past few years. However, the functions of mobile apps are varied and the designs of them are not well understood by end users, especially the activities and functions related to user privacy. Therefore, understanding how much danger of mobile apps with respect to privacy violation to mobile users is becomes a critical issue when people use mobile devices. In this paper, we evaluate the mobile app privacy violation of mobile users by computing the danger coefficient. In order to help people reduce the privacy leakage, we combine both the user preference to mobile apps and the privacy risk of apps and propose a mobile app usage recommendation method named AppURank to recommend the secure apps with the same function as the “dangerous” one for people use. The evaluation results show that our recommendation can reduce the privacy leakage by 50%.

KLASIFIKASI SMS SPAM MENGGUNAKAN SUPPORT VECTOR MACHINE

2019 ◽  
Vol 15 (2) ◽  
pp. 275-280
Author(s):  
Agus Setiyono ◽  
Hilman F Pardede
Keyword(s):  
Data Mining ◽  
Support Vector Machine ◽  
Decision Tree ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Support Vector ◽  
Spam Detection ◽  
Support Vector Machine Algorithm ◽  
Data Mining Techniques ◽  
To Receive

It is now common for a cellphone to receive spam messages. Great number of received messages making it difficult for human to classify those messages to Spam or no Spam.  One way to overcome this problem is to use Data Mining for automatic classifications. In this paper, we investigate various data mining techniques, named Support Vector Machine, Multinomial Naïve Bayes and Decision Tree for automatic spam detection. Our experimental results show that Support Vector Machine algorithm is the best algorithm over three evaluated algorithms. Support Vector Machine achieves 98.33%, while Multinomial Naïve Bayes achieves 98.13% and Decision Tree is at 97.10 % accuracy.

scholarly journals A Longitudinal Study of Pervasive Display Personalisation

2021 ◽  
Vol 28 (1) ◽  
pp. 1-45
Author(s):  
Mateusz Mikusz ◽  
Peter Shaw ◽  
Nigel Davies ◽  
Petteri Nurmi ◽  
Sarah Clinch ◽  
...  
Keyword(s):  
Longitudinal Study ◽  
Mobile Devices ◽  
Potential User ◽  
Mobile Users ◽  
Prior Work ◽  
Physical Spaces

Widespread sensing devices enable a world in which physical spaces become personalised in the presence of mobile users. An important example of such personalisation is the use of pervasive displays to show content that matches the requirements of proximate viewers. Despite prior work on prototype systems that use mobile devices to personalise displays, no significant attempts to trial such systems have been carried out. In this article, we report on our experiences of designing, developing and operating the world’s first comprehensive display personalisation service for mobile users. Through a set of rigorous quantitative measures and 11 potential user/stakeholder interviews, we demonstrate the success of the platform in realising display personalisation, and offer a series of reflections to inform the design of future systems.

Tracking of Wearable IoT Devices Through WAP Using Intelligent Rule-Based Location Aware Approach

2021 ◽  
Vol 20 (Supp01) ◽  
pp. 2140005
Author(s):  
L. Sai Ramesh ◽  
S. Shyam Sundar ◽  
K. Selvakumar ◽  
S. Sabena
Keyword(s):  
Mobile Devices ◽  
Task Completion ◽  
End User ◽  
Access Points ◽  
The Public ◽  
Location Aware ◽  
Unique Identity ◽  
Iot Devices ◽  
Public Environment ◽  
Specific Scenario

Usage of the internet is increasing in the daily life of humans due to the need for speedy task completion for their daily services. Most of the living time is spent in some indoor environment which provides WiFi which is the basic need of internet connectivity using Wireless Access Points (WAP). Nowadays, most of the devices are IoT-based ones, which connect with the outer world through the access points in the existing environment. The wearable IoT devices may be misplaced somewhere and we need a specific scenario which helps to identify the misplaced mobile devices based on access points where they are connected by their unique identity such as MAC address. Most of the time, unrestricted WiFi access provided in the public environment is used by the end-user. In that scenario, the tracking of misplaced mobile devices is creating an issue when the WiFi is in switch-off mode. This paper proposes a technique for tracking a mobile device by using a location-aware approach with KNN and intelligent rules by tracking the channel accessed by the user to find the misplaced path by examining the device connected WAP positions.

scholarly journals Enabling Efficient Decentralized and Privacy Preserving Data Sharing in Mobile Cloud Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Jiawei Zhang ◽  
Ning Lu ◽  
Teng Li ◽  
Jianfeng Ma
Keyword(s):  
Cloud Computing ◽  
Access Control ◽  
Mobile Devices ◽  
Data Sharing ◽  
Mobile Cloud Computing ◽  
High Efficiency ◽  
Mobile Cloud ◽  
User Privacy ◽  
Access Policy ◽  
Fine Grained

Mobile cloud computing (MCC) is embracing rapid development these days and able to provide data outsourcing and sharing services for cloud users with pervasively smart mobile devices. Although these services bring various conveniences, many security concerns such as illegally access and user privacy leakage are inflicted. Aiming to protect the security of cloud data sharing against unauthorized accesses, many studies have been conducted for fine-grained access control using ciphertext-policy attribute-based encryption (CP-ABE). However, a practical and secure data sharing scheme that simultaneously supports fine-grained access control, large university, key escrow free, and privacy protection in MCC with expressive access policy, high efficiency, verifiability, and exculpability on resource-limited mobile devices has not been fully explored yet. Therefore, we investigate the challenge and propose an Efficient and Multiauthority Large Universe Policy-Hiding Data Sharing (EMA-LUPHDS) scheme. In this scheme, we employ fully hidden policy to preserve the user privacy in access policy. To adapt to large scale and distributed MCC environment, we optimize multiauthority CP-ABE to be compatible with large attribute universe. Meanwhile, for the efficiency purpose, online/offline and verifiable outsourced decryption techniques with exculpability are leveraged in our scheme. In the end, we demonstrate the flexibility and high efficiency of our proposal for data sharing in MCC by extensive performance evaluation.

WIC Cash Value Voucher Redemption Behavior in Jefferson County, Alabama, and Its Association With Fruit and Vegetable Consumption

2017 ◽  
Vol 32 (2) ◽  
pp. 325-333 ◽  
Author(s):  
Chelsea R. Singleton ◽  
William Opoku-Agyeman ◽  
Ermanno Affuso ◽  
Monica L. Baskin ◽  
Emily B. Levitan ◽  
...  
Keyword(s):  
Vegetable Intake ◽  
Vegetable Consumption ◽  
Farmers Markets ◽  
Grocery Stores ◽  
Jefferson County ◽  
Fruit And Vegetable ◽  
Cross Sectional ◽  
Supplemental Nutrition Program ◽  
Study Participants ◽  
Cash Value Voucher

Purpose: To examine cash value voucher (CVV) redemption behavior and its association with fruit and vegetable (FV) consumption among women who participate in the Supplemental Nutrition Program for Women, Infants, and Children (WIC). Design: Cross-sectional. Setting: Jefferson County, Alabama. Participants: Between October 2014 and January 2015, 300 women (mean age: 27.6 years; 66.8% non-Hispanic black; 45.1% obese) who participated in the Birmingham WIC program were surveyed. Measures: Self-reported information on demographics, produce shopping behaviors, and residential access to fresh produce retailers (eg, supermarkets and farmers markets) was examined. Fruit and vegetable intake was collected via the Block Fruit–Vegetable–Fiber screener. Participants who self-reported redeeming the WIC CVV in each of the 3 prior months were classified as regular redeemers. Analysis: Multivariable-adjusted regression models were used to examine associations between variables of interest and regular WIC CVV redemption. Results: There were 189 (63.0%) study participants classified as regular WIC CVV redeemers. Regular redeemers and other participants (ie, irregular redeemers and nonredeemers) were similar with respect to demographics. Regular redeemers were more likely to use grocery stores to purchase FVs ( P = .003) and consumed significantly more servings of FVs per day (β = .67; standard error = 0.24; P = .007). Conclusion: Regular WIC CVV redemption was associated with some produce shopping behaviors and increased FV consumption and among WIC participants in Jefferson County, Alabama.

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