Implementation of Novel Machine Learning Methods for Analysis and Detection of Fake Reviews in Social Media
2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS),
Год журнала:
2023,
Номер
unknown, С. 243 - 250
Опубликована: Март 23, 2023
Now-a-days
social
media
plays
a
key
role
in
our
daily
life.
For
many
things
we
rely
on
this
media.
This
very
crucial
several
fields.
People
started
believing
the
which
are
written
internet
before
taking
their
decisions,
such
as
having
look
reviews
for
various
purposes
like
buying
product
online
or
booking
hotel
room
vacation
visiting
place,
all
these
people
by
people.
By
there
will
be
advantages
well
disadvantages.
Some
to
improve
company
standards
high
lightening
products,
they
generate
few
fake
attracts
users
towards
them
and
that
starts
choosing
them.
A
target
object's
positive
ratings
may
draw
more
consumers
boost
sales,
whereas
negative
result
less
demand
lower
sales.
Our
research
aims
determine
if
review
is
genuine
fraudulent.
To
avoid
go
with
need
detection
system.
In
system
some
machine
learning
techniques
used.
The
proposed
method
consists
of
algorithms.
They
performed
benchmark
analysis
different
types
(1)
traditional
ML
algorithms
logistic
regression
(LR),
support
vector
machines
(SVM),
decision
trees
(DT),
Naive
bayes
(NB),
random
forests
(RF),
&
XG
Boost
(XGB),
an
ensemble
approach
algorithms,
(2)
cutting-edge
bidirectional
long
short-term
memory
(BIIS
TM),
etc.
These
assist
identifying
bogus
reviews.
contrasted
one
another
provide
precise
results.
Язык: Английский
Qualitative Exploration of Data Security Risks in Mobile Cloud Computing for Higher Education
Security and Privacy,
Год журнала:
2025,
Номер
8(2)
Опубликована: Фев. 16, 2025
ABSTRACT
Mobile
cloud
computing
(MCC)
represents
a
groundbreaking
approach
to
education,
significantly
influencing
teaching
and
learning
dynamics.
Educational
institutions
stand
gain
from
MCC
by
facilitating
the
storage
of
educational
data
granting
users
capability
access
this
various
locations
at
any
time.
However,
several
challenges
must
be
addressed
ensure
successful
adoption
comprehensive
integration
on
global
scale.
Among
these
challenges,
security
emerges
as
critical
concern,
presenting
substantial
risks
effective
implementation
MCC.
This
study
seeks
explore
potential
associated
with
in
Palestinian
Higher
Education
Institutions
(HEIs).
In
addition,
research
outlines
strategies
that
integrate
technological
organizational
measures
address
identified
risks.
Employing
qualitative
methodology,
included
in‐depth
semi‐structured
interviews
10
IT
experts
professionals
HEIs
local
service
providers,
selected
for
their
expertise
Thematic
analysis
was
used
interpret
interview
identify
prevalent
themes,
supported
NVivo12
software.
Findings
indicate
most
participating
perceive
posing
significant
Furthermore,
notable
lack
awareness
exists
among
students
staff
regarding
risks,
underscoring
necessity
ongoing
training
initiatives
enhance
understanding
issues
related
Additionally,
such
loss,
breaches,
location,
backup
restoration,
segregation,
scavenging
influence
HEIs.
The
highlights
importance
employing
technical
tools
mitigate
effectively.
universities
face
range
managing
inherent
MCC,
including
limitations,
cost
management,
gaps
knowledge
expertise,
administrative
hurdles,
user‐related
concerns.
maximization
its
benefits,
ultimately
leading
improved
operational
outcomes.
Through
initiative,
will
valuable
insights
assist
them
overcoming
making
progress
initial
phases
implementation,
thereby
ensuring
smoother
transition
technology.
Moreover,
also
provide
benefits
providers
offering
specific
facilitate
development
tailored
services
solutions
adequately
unique
needs
institutions.
Язык: Английский
The Implementation of Transfer Learning by Convolution Neural Network (CNN) for Recognizing Facial Emotions
Journal of Advanced Research in Applied Sciences and Engineering Technology,
Год журнала:
2023,
Номер
32(2), С. 255 - 276
Опубликована: Сен. 7, 2023
The
primary
objective
of
this
study
is
to
develop
a
real-time
system
that
can
predict
the
emotional
states
an
individual
who
commonly
undergoes
various
experiences.
methodology
suggested
in
research
for
detecting
facial
expressions
involves
integration
transfer
learning
techniques
incorporate
convolutional
neural
networks
(CNNs),
along
with
parameterization
approach
minimizes
number
parameters.
FER-2013,
JAFFE,
and
CK+
datasets
were
jointly
used
train
CNN
architecture
detection,
which
broadened
range
may
be
recognized.
proposed
model
has
capability
identify
emotions,
including
but
not
limited
happiness,
fear,
surprise,
anger,
contempt,
sadness,
neutrality.
Several
methods
employed
assess
efficacy
model's
performance
study.
experimental
results
indicate
surpasses
previous
studies
terms
both
speed
accuracy.
Язык: Английский
Wireless 6G Cloud Communication Based Security Analysis Using Machine Learning in Internet of Medical Things (IoMT)
Jicheng Chen,
Yi‐Han Xu,
Xun Zhu
и другие.
Wireless Personal Communications,
Год журнала:
2024,
Номер
unknown
Опубликована: Май 15, 2024
Язык: Английский
Enhancing mobile data security using red panda optimized approach with chaotic fuzzy encryption in mobile cloud computing
Concurrency and Computation Practice and Experience,
Год журнала:
2024,
Номер
36(23)
Опубликована: Июль 30, 2024
Summary
Smartphone
devices
have
occupied
an
indispensable
place
in
human
life.
These
some
restrictions,
like
short
lifetime
of
battery,
imperfect
computation
power,
less
memory
size
and
unpredictable
network
connectivity.
Hence,
a
number
methods
previously
presented
to
decrease
these
restrictions
as
well
increase
the
battery
lifespan
with
help
offloading
strategy.
This
manuscript
proposes
new
enhancing
mobile
data
security
using
red
panda
optimized
approach
chaotic
fuzzy
encryption
cloud
computing
(RPO‐CFE‐SMC)
offload
intensive
tasks
from
device
cloud.
The
proposed
model
utilizes
optimization
algorithm
(RPOA)
scale
dynamically
decision
under
energy
consumption,
CPU
utilization,
execution
time,
usage
parameters.
Before
work
is
transferred
cloud,
innovative
layer
applied
for
encrypting
AES
(CFE)
technology.
RPO‐CFE‐SMC
method
provides
20.63%,
25.25%,
25.28%,
32.47%
lower
time
23.66%,
24.25%,
26.47%
consumption
compared
existing
EFFORT‐SMC,
EESH‐SMC,
CP‐ABE‐SMC
models
respectively.
In
conclusion,
simulation
results
prove
that
improved
efficiency
enhanced
protection
encryption.
Язык: Английский
Usage of Computer Aided Methods for Detection and Evaluation of Breast Cancer in Mammograms
Опубликована: Сен. 18, 2024
Язык: Английский
Big Data Analytics Survey: Environment, Technologies, and Use Cases
Опубликована: Сен. 18, 2024
Язык: Английский
Dimensions of Automated ETL Management: A Contemporary Literature Review
2022 International Conference on Automation, Computing and Renewable Systems (ICACRS),
Год журнала:
2022,
Номер
unknown, С. 1292 - 1297
Опубликована: Дек. 13, 2022
ETL
solutions
are
becoming
more
widely
used
because
of
the
increasing
complexity
data
systems
and
importance
high-quality
sources
processing
for
making
decisions.
The
raw
is
retrieved
placed
into
a
designated
warehouse
efficient
information
analysis
processing.
Using
management
technologies
to
acquire
insights
functional
operational
elements
one
critical
components
software
engineering
in
present
environment.
There
need
improve
performance
real-time
applications.
However,
several
scholarly
business
investigations
have
been
efficacy
dynamics
technologies.
As
result,
it
essential
look
at
methods
effectiveness
processes
meet
immediate
demands
operations.
This
paper
explores
existing
systems'
history,
constraints,
potential,
how
machine
learning
models
integrated
processes.
as
evidenced
by
review
relevant
academic
literature,
there
widespread
support
using
perfect
Although
many
can
be
helpful
processing,
only
tiny
fraction
market
products
use
them
all.
Machine
learning-based
optimize
ETL-based
management,
concentrating
on
limits
future
potential.
Язык: Английский