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EditorialLocation-Based Mobile Marketing Innovations 2018
Jaegeol Yim ,1 Subramaniam Ganesan ,2 and Byeong Ho Kang 3
1Professor Emeritus, Department of Computer Engineering, Dongguk
University, Gyeongju, Republic of Korea2Professor, Electrical and
Computer Engineering, Oakland University, Rochester, USA3Professor,
School of Engineering and ICT, University of Tasmania, Hobart,
Australia
Correspondence should be addressed to Jaegeol Yim;
[email protected]
Received 15 April 2019; Accepted 15 April 2019; Published 28
April 2019
Copyright © 2019 Jaegeol Yim et al. #is is an open access
article distributed under the Creative Commons Attribution
License,which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly
cited.
#e increasing complexity of the industry means thatmarketers
must now be experts not only in marketing,but also in people, data,
delivery platforms, and mobilelocation-based marketing.
#e objective of location-based marketing via mobiledevices is to
encourage those activities, as well as to drivefoot traffic, share
discounts, and build customer loyalty.#e mobile devices are used to
gather information aboutnearby businesses including reviews,
directions, callingthe business, and using the businesses’ mobile
app. Withlocation-based mobile marketing, the business is easy
tofind and have skillfully combined location-based mar-keting with
an overall targeted marketing approach thatincludes social media,
push notifications, e-mail newsletters,and even offline
marketing.
#e objective of this special issue is to bring togetherresearch
contributions of unpublished research on the recentdevelopment and
innovations about the location-basedservice mobile marketing. #is
aims to facilitate and supportresearch in the current e-commerce
innovation that makesbusiness easy, engaging, and at hand of the
consumers.
#e paper “#e Identification of Marketing PerformanceUsing Text
Mining of Airline Review Data” aims to firstlyextract major
keywords using text mining method, secondlyto identify prominent
keyword from the keywords extractedfrom text mining analysis, and
then to confirm differences ininfluences of the keywordswhich
affect corporate performance.
In the paper “Dilemma and Solution of TraditionalFeature
Extraction Methods Based on Inertial Sensors,”after analyzing the
difference of these indistinguishablemovements, the authors propose
several new features toimprove accuracy of recognition. #ey compare
the traditionalfeatures and their custom features. In addition,
they examined
whether the time domain features and frequency domainfeatures
based on acceleration and angular velocity aredifferent.
In the paper “CEnsLoc: Infrastructure-Less Indoor Local-ization
Methodology Using GMM Clustering-Based Clas-sification Ensembles,”
the authors propose CEnsLoc, a neweasy to train-and-deploy Wi-Fi
localization methodologyestablished on GMM clustering and random
forest ensembles(RFE). Principal component analysis was applied for
dimen-sion reduction of raw data. Conducted
experimentationdemonstrates that it provides 97% accuracy for room
pre-diction, whereas artificial neural networks, k-nearest
neigh-bors, K∗, FURIA, and DeepLearning4J-based
localizationsolutions provided mean 85%, 91%, 90%, 92%, and
73%accuracy on the collected real-world dataset, respectively.
Itdelivers high room level accuracy with negligible responsetime,
making it viable and befitted for real-time applications.
In “Location Privacy Protection Research Based onQuerying
Anonymous Region Construction for SmartCampus,” the user’s query
range is introduced to presenta novel anonymous region construction
scheme. #e anon-ymous server first generates the original anonymous
sub-regions according to the user’s privacy requirements and
thenmerges them to construct the anonymity regions submitted toLSP
based on the size of corresponding querying regions. #esecurity and
experiment analyses show that the proposedscheme not only protects
the user’s privacy effectively but alsodecreases the area of LSP
querying regions and the region-constructing time, improving the
quality of service for smartcampus.
#e paper “Consumers Team Detection Model Based onTrust for
Multi-Level” proposes a novel local communitydetection model
E-MLCD. It is jointly based on the multilevel
HindawiMobile Information SystemsVolume 2019, Article ID
2164708, 2 pageshttps://doi.org/10.1155/2019/2164708
mailto:[email protected]://orcid.org/0000-0002-6181-8434http://orcid.org/0000-0003-0233-9940http://orcid.org/0000-0003-3476-8838https://creativecommons.org/licenses/by/4.0/https://creativecommons.org/licenses/by/4.0/https://creativecommons.org/licenses/by/4.0/https://creativecommons.org/licenses/by/4.0/https://creativecommons.org/licenses/by/4.0/https://creativecommons.org/licenses/by/4.0/https://creativecommons.org/licenses/by/4.0/https://doi.org/10.1155/2019/2164708
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properties and the strength of similarity of multilevel
socialinteraction among communities. By studying three real-world
multilevel social networks and specific QQ zonemarketing data, the
model defines a new metric of simi-larity strength based on
community structure similarity.Comparison with other
state-of-the-art detection methodsdemonstrates E-MLCD’s ability to
detect communities moreeffectively.
In “RoC: Robust and Low-Complexity Wireless IndoorPositioning
Systems forMultifloor Buildings Using LocationFingerprinting
Techniques,” the authors propose a novelintegrated framework for
wireless indoor positioning sys-tems based on a location
fingerprinting technique which iscalled the robust and low
complexity indoor positioningsystems framework (RoC framework). #e
proposed inte-grated framework consists of two essential indoor
positioningprocesses: the system design process and the
localizationprocess. #e RoC framework aims to achieve robustnessin
the system design structure and reliability of the targetlocation
during the online estimation phase either undera normal situation
or when some reference nodes (RNs)have failed.
#e paper “An Indoor Location-Based Positioning SystemUsing
Stereo Vision with the Drone Camera” proposes theindoor
location-based drone controlling method that doesnot require the
traditional remote controller and can beapplied to various services
such as a group flight.
In the paper “Research on Precision Marketing Modelof Tourism
Industry Based on User’s Mobile BehaviorTrajectory,” data mining
clustering technology is used toanalyze the characteristics of
user’s mobile behavior tra-jectories, and the precise
recommendation system of tourismis constructed to support for
tourism decision making. It cantarget the tourist group for the
precise marketing and maketourist travel smarter.
#e paper “A Case Study Analysis of Clothing ShoppingMall for
Customer Design Participation Service and De-velopment of Customer
Editing User Interface” discusses aservice related to the
convergence of the traditional clothingindustry with ITand a
service wherein CT is converged withsystems that allow customers to
participate in the designwork and share the designs they have
created. #e resultsshow that both production method and production
capacitylargely affect the user interface of apparel platform
services,with customer freedom significantly correlated with
theirfunctional roles. Moreover, the lead index is shown to be
oneof the factors restraining customer freedom.
#e paper “Malaria Vulnerability Map Mobile SystemDevelopment
Using GIS-Based Decision-Making Technique”aims to improve the lack
of GIS information use and com-patibility of multiplatform which
represented limits thatexisting malaria risk analysis tools have.
For this, theauthors developed mobile web-based malaria
vulnerabilitymap system using GIS information. #is system
consistsof system database construction, malaria risk
calculationfunction, visual expression function, and website and
mobileapplication.
In the paper “A Study onRemoving CloudDrift of Sky-SeaInfrared
Image Based on Agent,” a new shadow extraction
method is proposed.#is method tests and removes cloud ofinfrared
images based on cloud characteristics from infraredsky-sea images.
#rough grey value characteristics of cloud,we can find and use
reactive agent layer structure and classifymany agents used for
local image cloud searching andmanageagents used for coordinating
many cloud searching agent.
#e paper titled “From Reputation Perspective: A Hy-brid Matrix
Factorization for QoS Prediction in Location-Aware Mobile Service
Recommendation System” proposes ahybrid matrix factorization method
integrated location andreputation information (LRMF) to predict the
unattainableQoS values. #e proposed method effectively reduces
theimpact of unreliable users on QoS prediction and makescredible
mobile service recommendation.
#e paper “Location-Based Test Case Prioritization forSoftware
Embedded in Mobile Devices Using the Law ofGravitation” uses a
smart mall as a scenario to design anovel location-based test case
prioritization (TCP) tech-nique for software embedded inmobile
devices using the lawof gravitation. An empirical evaluation is
presented by usingone industrial project. #e observation,
underlying the ex-perimental results, is that the proposed TCP
approach per-forms better than traditional TCP techniques. In
addition,besides location information, the level of devices is also
animportant factor which affects the prioritization efficiency.
#e paper “Profile-Based Ad Hoc Social NetworkingUsing Wi-Fi
Direct on the Top of Android” presents an ar-chitecture and
implementation of social networks on com-mercially available mobile
devices that allow broadcastingname and a limited number of
keywords representing users’interests without any connection in a
nearby region to fa-cilitate matching of interests. #e broadcasting
region cre-ates a digital aura and is limited by Wi-Fi region that
isaround 200 meters.
We are very happy to publish this special issue of themobile
information systems. #is issue contains 14 articles.Achieving such
a high quality of papers would have beenimpossible without the huge
work that was undertaken bythe Editorial Board members and External
Reviewers. Wetake this opportunity to thank them for their great
supportand cooperation.
Conflicts of Interest
#e editors declare that they have no conflicts of interest.
Jaegeol YimSubramaniam Ganesan
Byeong Ho Kang
2 Mobile Information Systems
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