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1ICA, Nonlinear Independent Component Analysis, Unsupervised Learning, Redundancy Reduction
http://people.idsia.ch/~juergen/ica.html
7 years ago by @becker
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linear
component
independent
ica
machine
learning
analysis
pca
non
from:hotho
nonlinear
linearcomponentindependenticamachinelearninganalysispcanonfrom:hothononlinear
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1SVD & PCA using R
SVD & PCA and realtion in R, but does not calculate PCA from SVD
11 years ago by @becker
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svd
principal
component
singular
decomposition
analysis
value
pca
svdprincipalcomponentsingulardecompositionanalysisvaluepca
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2PCA and SVD
An introduction to SVD and PCA and its comparison.
11 years ago by @becker
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svd
principal
component
singular
decomposition
analysis
value
pca
svdprincipalcomponentsingulardecompositionanalysisvaluepca
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1ryananeff/DGCA: DGCA 2.0: Highly Parallel and Memory-efficient Differential Correlation analysis
https://github.com/ryananeff/DGCA
4 years ago by @becker
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fast
parallel
gene
correlation
analysis
differential
paper:fastcor
dgca
fastparallelgenecorrelationanalysisdifferentialpaper:fastcordgca
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1Propensity Score Analysis | Columbia Public Health
https://www.publichealth.columbia.edu/research/population-health-methods/propensity-score-analysis
2 years ago by @becker
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score
propensity
tutorial
simple
biomedicine
analysis
explanation
matching
scorepropensitytutorialsimplebiomedicineanalysisexplanationmatching
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1shafferm/SCNIC: Sparse Cooccurence Network Investigation for Compositional data
https://github.com/shafferm/SCNIC
3 years ago by @becker
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co-occurrence
data
correlation
compositional
positive
analysis
project:fastcor
network
coocurrence
co-occurrencedatacorrelationcompositionalpositiveanalysisproject:fastcornetworkcoocurrence
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1Varimax PCA
https://twitter.com/karlrohe/status/1513528399201021965?t=UhJUk71F5_eYfusM7qY-YA&s=19
3 years ago by @becker
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toread
inference
analysis
pca
varimax
factor
toreadinferenceanalysispcavarimaxfactor
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1Principal Component Analyses (PCA)-based findings in population genetic studies are highly biased and must be reevaluated
https://www.nature.com/articles/s41598-022-14395-4#citeas
2 years ago by @becker
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component
principle
evaluation
critique
analysis
pca
componentprincipleevaluationcritiqueanalysispca
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3Web log analysis: a review of a decade of studies about information acquisition, inspection and interpretation of user interaction
M. Agosti, F. Crivellari, and G. Di Nunzio. Data Mining and Knowledge Discovery, 24 (3): 663--696 (2012)
8 years ago by @becker
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tagging
log
social
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inthesis
future
predict
tag
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bookmarking
tagginglogsocialpredictionsdissanalysiswebinthesisfuturepredicttagreviewsurveytrendsbibsonomybookmarking
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1Web User Behavior Analysis
P. Asenjo. UNIVERSIDAD DE CHILE, (2011)
8 years ago by @becker
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web
chain
inthesis
diss
model
analysis
relatedwork
user
markov
variable
behavior
webchaininthesisdissmodelanalysisrelatedworkusermarkovvariablebehavior
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1Fouille de données médicales: Analyse et prédiction de données sur les maladies cardio-vasculaires
N. Barret, V. Acier, J. Reisser, and N. Medjedel. (20xx)
5 years ago by @becker
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pysubgroup
subgroup
application
analysis
pysubgroupsubgroupapplicationanalysis
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8Characterizing User Behavior in Online Social Networks
F. Benevenuto, T. Rodrigues, M. Cha, and V. Almeida. Conference on Internet Measurement Conference ( SIGCOMM), page 49--62. New York, NY, USA, ACM, (2009)
8 years ago by @becker
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citedby:scholar:timestamp:2017-2-4
inthesis
social
diss
analysis
network
bevahior
descriptive
markov
citedby:scholar:count:663
citedby:scholar:timestamp:2017-2-4inthesissocialdissanalysisnetworkbevahiordescriptivemarkovcitedby:scholar:count:663
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3Stylometric analysis of scientific articles
S. Bergsma, M. Post, and D. Yarowsky. Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, page 327--337. Association for Computational Linguistics, (2012)
7 years ago by @becker
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citedby:scholar:count:63
gender
scientific
author
paper:country:cite
analysis
non
research
writing
native
profiling
paper:country
nonnative
articles
citedby:scholar:timestamp:2018-1-10
stylometric
citedby:scholar:count:63genderscientificauthorpaper:country:citeanalysisnonresearchwritingnativeprofilingpaper:countrynonnativearticlescitedby:scholar:timestamp:2018-1-10stylometric
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1Activity-Based Modeling of Travel Demand
C. Bhat, and F. Koppelman. page 35--61. Springer US, Boston, MA, (1999)
8 years ago by @becker
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based
geo
modeling
citedby:scholar:count:139
inthesis
acitvity
diss
analysis
spatial
demand
citedby:scholar:timestamp:2017-2-7
travel
basedgeomodelingcitedby:scholar:count:139inthesisacitvitydissanalysisspatialdemandcitedby:scholar:timestamp:2017-2-7travel
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1Sociological Inquiry Principles: Qualitative and Quantitative Methods
A. Blackstone. Flat World Knowledge, Irvington, NY, USA, (2012)
8 years ago by @becker
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induction
inductive
citable
inthesis
reasoning
deduction
deductive
diss
analysis
research
inductioninductivecitableinthesisreasoningdeductiondeductivedissanalysisresearch
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1Estimating batch effect in Microarray data with Principal Variance Component Analysis (PVCA) method
P. Bushel, and J. Li. (2015)
3 years ago by @becker
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citedby:scholar:timestamp:2022-3-18
principal
component
citedby:scholar:count:1
variance
pvca
test
analysis
pca
citedby:scholar:timestamp:2022-3-18principalcomponentcitedby:scholar:count:1variancepvcatestanalysispca
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1Sequence discrimination using phase-type distributions
CALLUT, and J, #233, rome, DUPONT, and and Pierre. Springer, (2006)
8 years ago by @becker
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sequence
phase
chain
discrimination
analysis
distribution
kersting
markov
type
sequencephasechaindiscriminationanalysisdistributionkerstingmarkovtype
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2Multi-dimensional regression analysis of time-series data streams
Y. Chen, G. Dong, J. Han, B. Wah, and J. Wang. Proceedings of the 28th international conference on Very Large Data Bases, page 323--334. VLDB Endowment, (2002)
11 years ago by @becker
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mining
s:2013-12-18_time-series-mining
dimensional
regression
series
time
analysis
multi
minings:2013-12-18_time-series-miningdimensionalregressionseriestimeanalysismulti
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1Symbolic time series analysis for anomaly detection: a comparative evaluation
S. Chin, A. Ray, and V. Rajagopalan. Signal Processing, 85 (9): 1859--1868 (2005)
11 years ago by @becker
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anomaly
detection
series
s:2013-12-10_anomaly
time
analysis
anomalydetectionseriess:2013-12-10_anomalytimeanalysis
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3Imaxes: Immersive axes as embodied affordances for interactive multivariate data visualisation
M. Cordeil, A. Cunningham, T. Dwyer, B. Thomas, and K. Marriott. Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology, page 71--83. (2017)
3 years ago by @becker
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virtual
citedby:scholar:count:140
reality
data
analysis
immermind
m:
plots
citedby:scholar:timestamp:2022-1-11
m:id:immermind:coordinate:y:134.9595603942871
m:id:immermind:node
vr
m:id:immermind:coordinate:x:-378.8338394165039
virtualcitedby:scholar:count:140realitydataanalysisimmermindm:plotscitedby:scholar:timestamp:2022-1-11m:id:immermind:coordinate:y:134.9595603942871m:id:immermind:nodevrm:id:immermind:coordinate:x:-378.8338394165039
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3Self-similarity in World Wide Web traffic: evidence and possible causes
M. Crovella, and A. Bestavros. IEEE/ACM Transactions on networking, 5 (6): 835--846 (1997)
8 years ago by @becker
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web
inthesis
navigation
diss
analysis
citedby:scholar:count:3347
traffic
citedby:scholar:timestamp:2017-5-4
webinthesisnavigationdissanalysiscitedby:scholar:count:3347trafficcitedby:scholar:timestamp:2017-5-4
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1Massive Social Network Analysis: Mining Twitter for Social Good.
D. Ediger, K. Jiang, J. Riedy, D. Bader, C. Corley, R. Farber, and W. Reynolds. ICPP, page 583-593. IEEE Computer Society, (2010)
13 years ago by @becker
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twitter
seminar
winter
2011
analysis
graph
selected
twitterseminarwinter2011analysisgraphselected
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3Web Path Recommendations Based on Page Ranking and Markov Models
M. Eirinaki, M. Vazirgiannis, and D. Kapogiannis. International Workshop on Web Information and Data Management, page 2--9. New York, NY, USA, ACM, (2005)
8 years ago by @becker
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chain
inthesis
navigational
prediction
page
diss
model
analysis
rank
markov
chaininthesisnavigationalpredictionpagedissmodelanalysisrankmarkov
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2Complex time series analysis of PM10 and PM2. 5 for a coastal site using artificial neural network modelling and k-means clustering
M. Elangasinghe, N. Singhal, K. Dirks, J. Salmond, and S. Samarasinghe. Atmospheric Environment, (2014)
7 years ago by @becker
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means
citedby:scholar:count:44
neural
pm2.5
kmeans
k
analysis
pm25
network
pm10
timeseries
clustering
p2map
nn
k-means
citedby:scholar:timestamp:2018-3-13
meanscitedby:scholar:count:44neuralpm2.5kmeanskanalysispm25networkpm10timeseriesclusteringp2mapnnk-meanscitedby:scholar:timestamp:2018-3-13
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7Mining interesting knowledge from weblogs: a survey
F. Facca, and P. Lanzi. Data & Knowledge Engineering, 53 (3): 225--241 (2005)
8 years ago by @becker
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web
log
access
inthesis
mining
citedby:scholar:timestamp:2017-4-20
sequential
pattern
diss
analysis
citedby:scholar:count:389
weblogaccessinthesisminingcitedby:scholar:timestamp:2017-4-20sequentialpatterndissanalysiscitedby:scholar:count:389
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1DiffCorr: an R package to analyze and visualize differential correlations in biological networks
A. Fukushima. Gene, 518 (1): 209--214 (2013)
2 years ago by @becker
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correlation
citedby:scholar:count:142
analysis
citedby:scholar:timestamp:2022-9-18
differential
paper:fastcor
correlationcitedby:scholar:count:142analysiscitedby:scholar:timestamp:2022-9-18differentialpaper:fastcor
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1DCARS: differential correlation across ranked samples
S. Ghazanfar, D. Strbenac, J. Ormerod, J. Yang, and E. Patrick. Bioinformatics, 35 (5): 823--829 (2019)
2 years ago by @becker
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correlation
citedby:scholar:count:5
analysis
citedby:scholar:timestamp:2022-9-18
differential
paper:fastcor
correlationcitedby:scholar:count:5analysiscitedby:scholar:timestamp:2022-9-18differentialpaper:fastcor
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1Sandpile on scale-free networks
K. Goh, D. Lee, B. Kahng, and D. Kim. Physical review letters, 91 (14): 148701 (2003)
13 years ago by @becker
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twitter
vito
analysis
network
twittervitoanalysisnetwork
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1DINGO: differential network analysis in genomics
M. Ha, V. Baladandayuthapani, and K. Do. Bioinformatics, 31 (21): 3413--3420 (2015)
3 years ago by @becker
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citedby:scholar:count:106
m:id:test2:node
citedby:scholar:timestamp:2022-4-27
analysis
m:id:test2:coordinate:y:-49.76913261413574
m:
m:id:test2:coordinate:x:177.40279006958008
network
differential
paper:fastcor
citedby:scholar:count:106m:id:test2:nodecitedby:scholar:timestamp:2022-4-27analysism:id:test2:coordinate:y:-49.76913261413574m:m:id:test2:coordinate:x:177.40279006958008networkdifferentialpaper:fastcor
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1PaintOmics 3: a web resource for the pathway analysis and visualization of multi-omics data
R. Hernández-de Diego, S. Tarazona, C. Mart\'ınez-Mira, L. Balzano-Nogueira, P. Furió-Tar\'ı, G. Pappas Jr, and A. Conesa. Nucleic acids research, 46 (W1): W503--W509 (2018)
3 years ago by @becker
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nalab
citedby:scholar:count:98
citedby:scholar:timestamp:2022-1-27
um1
pathway
analysis
nalabcitedby:scholar:count:98citedby:scholar:timestamp:2022-1-27um1pathwayanalysis
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1The Sourcebook for Teaching Science, Grades 6-12: Strategies, Activities, and Instructional Resources
N. Herr. Wiley, (2008)
8 years ago by @becker
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induction
inductive
citable
inthesis
reasoning
deduction
deductive
mixedtrails
diss
analysis
research
inductioninductivecitableinthesisreasoningdeductiondeductivemixedtrailsdissanalysisresearch
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1BioNetStat: a tool for biological networks differential analysis
V. Jardim, S. Santos, A. Fujita, and M. Buckeridge. Frontiers in genetics, (2019)
3 years ago by @becker
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citedby:scholar:count:13
citedby:scholar:timestamp:2022-4-27
analysis
network
differential
paper:fastcor
citedby:scholar:count:13citedby:scholar:timestamp:2022-4-27analysisnetworkdifferentialpaper:fastcor
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1An evaluation of activity-based travel analysis
R. Kitamura. Transportation, 15 (1): 9--34 (1988)
8 years ago by @becker
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based
inthesis
activity
diss
analysis
demand
travel
basedinthesisactivitydissanalysisdemandtravel
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2A characterization of online browsing behavior
R. Kumar, and A. Tomkins. International Conference on World Wide Web, page 561--570. ACM, (2010)
8 years ago by @becker
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toolbar
browsing,
analysis
pageviews,
toolbarbrowsing,analysispageviews,
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4Visualization and analysis of clickstream data of online stores for understanding web merchandising
J. Lee, M. Podlaseck, E. Schonberg, and R. Hoch. Data Mining and Knowledge Discovery, 5 (1/2): 59--84 (2001)
7 years ago by @becker
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shop
webshop
citedby:scholar:count:207
citedby:scholar:timestamp:2017-6-25
web
inthesis
navigation
diss
analysis
behavior
shopwebshopcitedby:scholar:count:207citedby:scholar:timestamp:2017-6-25webinthesisnavigationdissanalysisbehavior
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1DGCA: a comprehensive R package for differential gene correlation analysis
A. McKenzie, I. Katsyv, W. Song, M. Wang, and B. Zhang. BMC systems biology, 10 (1): 106 (2016)
4 years ago by @becker
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disruption
gene
citedby:scholar:count:55
correlation
paper:cordis
citedby:scholar:timestamp:2020-8-2
analysis
differential
paper:fastcor
dgca
disruptiongenecitedby:scholar:count:55correlationpaper:cordiscitedby:scholar:timestamp:2020-8-2analysisdifferentialpaper:fastcordgca
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3On the lack of typical behavior in the global Web traffic network
M. Meiss, F. Menczer, and A. Vespignani. Proceedings of the 14th international conference on World Wide Web, page 510--518. ACM, (2005)
7 years ago by @becker
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modeling
web
inthesis
related
citedby:scholar:timestamp:2017-8-9
work
citedby:scholar:count:35
diss
analysis
modelingwebinthesisrelatedcitedby:scholar:timestamp:2017-8-9workcitedby:scholar:count:35dissanalysis
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3Using sequential and non-sequential patterns in predictive web usage mining tasks
B. Mobasher, H. Dai, T. Luo, and M. Nakagawa. International Conference on Data Mining, page 669--672. IEEE, (2002)
8 years ago by @becker
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web
sequentual
access
inthesis
mining
usage
citedby:scholar:timestamp:2017-4-20
pattern
citedby:scholar:count:130
frequent
diss
analysis
websequentualaccessinthesisminingusagecitedby:scholar:timestamp:2017-4-20patterncitedby:scholar:count:130frequentdissanalysis
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3Taste Over Time: The Temporal Dynamics of User Preferences
J. Moore, S. Chen, D. Turnbull, and T. Joachims. Conference of the International Society for Music Information Retrieval Conference (ISMIR), page 401-406. (2013)
8 years ago by @becker
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sequence
music
inthesis
embedding
diss
analysis
logistic
markov
sequencemusicinthesisembeddingdissanalysislogisticmarkov
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7Is the Sample Good Enough? Comparing Data from Twitter's Streaming API with Twitter's Firehose.
F. Morstatter, J. Pfeffer, H. Liu, and K. Carley. ICWSM, (2013)
10 years ago by @becker
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firehose
streaming
comparison
twitter
api
analysis
firehosestreamingcomparisontwitterapianalysis
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17FolkTrails: Interpreting navigation behavior in a social tagging system
T. Niebler, M. Becker, D. Zoller, S. Doerfel, and A. Hotho. International on Conference on Information and Knowledge Management, page 2311--2316. New York, NY, USA, ACM, (2016)
8 years ago by @becker
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bmbf
myown
erp
diss
analysis
hyptrails
cv
inthesis
diss:allmypubs
navigation
bayes
hypothesis
folktrails
bibsonomy
selected
bmbfmyownerpdissanalysishyptrailscvinthesisdiss:allmypubsnavigationbayeshypothesisfolktrailsbibsonomyselected
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1Integrative pathway enrichment analysis of multivariate omics data
M. Paczkowska, J. Barenboim, N. Sintupisut, N. Fox, H. Zhu, D. Abd-Rabbo, M. Mee, P. Boutros, and J. Reimand. Nature communications, 11 (1): 1--16 (2020)
3 years ago by @becker
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nalab
citedby:scholar:timestamp:2022-1-27
citedby:scholar:count:53
um1
pathway
analysis
nalabcitedby:scholar:timestamp:2022-1-27citedby:scholar:count:53um1pathwayanalysis
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2Temporal Dynamics in Music Listening Behavior: A Case Study of Online Music Service
C. Park, and M. Kahng. 2010 IEEE/ACIS 9th International Conference on Computer and Information Science, page 573-578. (August 2010)
8 years ago by @becker
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music
inthesis
diss
analysis
temporal
descriptive
musicinthesisdissanalysistemporaldescriptive
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3Temporal Network Analysis of Literary Texts
S. Prado, S. Dahmen, A. Bazzan, P. Mac Carron, and R. Kenna. (2016)cite arxiv:1602.07275Comment: 17 pages, 11 figures.
8 years ago by @becker
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literature
kallimachos
centrality
analysis
network
temporal
literaturekallimachoscentralityanalysisnetworktemporal
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1Unsupervised spike detection and sorting with wavelets and superparamagnetic clustering
R. Quiroga, Z. Nadasdy, and Y. Ben-Shaul. Neural computation, 16 (8): 1661--1687 (2004)
11 years ago by @becker
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signal
detection
s:2013-12-10_anomaly
analysis
spike
signaldetections:2013-12-10_anomalyanalysisspike
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3Link prediction and path analysis using Markov chains
R. Sarukkai. Computer Networks, 33 (1): 377 -- 386 (2000)
8 years ago by @becker
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chain
inthesis
prediction
link
diss
model
analysis
markov
chaininthesispredictionlinkdissmodelanalysismarkov
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1To explain or to predict?
G. Shmueli, and others. Statistical Science, 25 (3): 289--310 (2010)
7 years ago by @becker
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explain
citedby:scholar:count:513
inthesis
data
citedby:scholar:timestamp:2017-7-10
predict
prediction
diss
analysis
explanation
explaincitedby:scholar:count:513inthesisdatacitedby:scholar:timestamp:2017-7-10predictpredictiondissanalysisexplanation
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1The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains
D. Shuman, S. Narang, P. Frossard, A. Ortega, and P. Vandergheynst. IEEE signal processing magazine, 30 (3): 83--98 (2013)
4 years ago by @becker
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signal
functional
cordis
processing
analysis
citedby:scholar:count:2114
citedby:scholar:timestamp:2020-9-4
dis
graph
signalfunctionalcordisprocessinganalysiscitedby:scholar:count:2114citedby:scholar:timestamp:2020-9-4disgraph
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1The discordant method: a novel approach for differential correlation
C. Siska, R. Bowler, and K. Kechris. Bioinformatics, 32 (5): 690--696 (2016)
2 years ago by @becker
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correlation
citedby:scholar:count:28
analysis
citedby:scholar:timestamp:2022-9-18
differential
paper:fastcor
correlationcitedby:scholar:count:28analysiscitedby:scholar:timestamp:2022-9-18differentialpaper:fastcor
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1Maternity Log study: a longitudinal lifelog monitoring and multiomics analysis for the early prediction of complicated pregnancy
J. Sugawara, D. Ochi, R. Yamashita, T. Yamauchi, D. Saigusa, M. Wagata, T. Obara, M. Ishikuro, Y. Tsunemoto, Y. Harada and 1 other author(s). BMJ open, 9 (2): e025939 (2019)
4 years ago by @becker
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log
monitoring
activity
complications
pregnancy
data
analysis
fetal
citedby:scholar:count:4
maternity
multiomics
prediction
citedby:scholar:timestamp:2020-8-11
lifelog
outcome
longitudinal
logmonitoringactivitycomplicationspregnancydataanalysisfetalcitedby:scholar:count:4maternitymultiomicspredictioncitedby:scholar:timestamp:2020-8-11lifelogoutcomelongitudinal
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1SPACEc: A Streamlined, Interactive Python Workflow for Multiplexed Image Processing and Analysis
Y. Tan, T. Kempchen, M. Becker, M. Haist, D. Feyaerts, Y. Xiao, G. Su, A. Rech, R. Fan, J. Hickey and 1 other author(s). bioRxiv (under review), (2024)
3 months ago by @becker
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image
myown
library
imaging
pipeline
python
spacec
analysis
single
cell
imagemyownlibraryimagingpipelinepythonspacecanalysissinglecell
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2Transactional log analysis: Online catalogs
J. Tolle. Annual International Conference on Research and Development in Information Retrieval, page 147-160. ACM, (1983)
8 years ago by @becker
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log
web
inthesis
catalog
online
diss
analysis
logwebinthesiscatalogonlinedissanalysis
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1Exploring Relations in Neuroscientific Literature using Augmented Reality: A Design Study
I. Troost, G. Tanhaei, L. Hardman, and W. Hürst. Designing Interactive Systems Conference 2021, page 266--274. (2021)
3 years ago by @becker
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literature
exploration
virtual
m:id:immermind:coordinate:x:52.87889862060547
reality
m:id:immermind:coordinate:y:-250.97742080688477
m:id:immermind:node
vr
analysis
immermind
m:
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3Survey on mining subjective data on the web
M. Tsytsarau, and T. Palpanas. Data Mining and Knowledge Discovery, (October 2011)
13 years ago by @becker
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sentiment
analysis
sentimentanalysis
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1Differential network analysis by simultaneously considering changes in gene interactions and gene expression
J. Tu, L. Ou-Yang, Y. Zhu, H. Yan, H. Qin, and X. Zhang. Bioinformatics, 37 (23): 4414--4423 (2021)
3 years ago by @becker
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citedby:scholar:count:3
citedby:scholar:timestamp:2022-4-27
analysis
network
differential
paper:fastcor
citedby:scholar:count:3citedby:scholar:timestamp:2022-4-27analysisnetworkdifferentialpaper:fastcor
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1Full correlation matrix analysis of fMRI data on Intel® Xeon Phi™ coprocessors
Y. Wang, M. Anderson, J. Cohen, A. Heinecke, K. Li, N. Satish, N. Sundaram, N. Turk-Browne, and T. Willke. SC'15: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, page 1--12. IEEE, (2015)
4 years ago by @becker
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functional
distributed
citedby:scholar:count:15
analysis
matrix
fmri
paper:fastcor
brain
parallel
connectivity
citedby:scholar:timestamp:2021-1-7
correlation
full
fcma
functionaldistributedcitedby:scholar:count:15analysismatrixfmripaper:fastcorbrainparallelconnectivitycitedby:scholar:timestamp:2021-1-7correlationfullfcma
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3Off the Beaten Tracks: Exploring Three Aspects of Web Navigation
H. Weinreich, H. Obendorf, E. Herder, and M. Mayer. International Conference on World Wide Web, page 133--142. New York, NY, USA, ACM, (2006)
8 years ago by @becker
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inthesis
navigation
diss
analysis
inthesisnavigationdissanalysis
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8Prediction of Happy Endings in German Novels
A. Zehe, M. Becker, L. Hettinger, A. Hotho, I. Reger, and F. Jannidis. Proceedings of the Workshop on Interactions between Data Mining and Natural Language Processing 2016, page 9-16. (July 2016)
8 years ago by @becker
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ending
literature
sentiment
myown
kallimachos
diss:allmypubs
happy
analysis
classification
endingliteraturesentimentmyownkallimachosdiss:allmypubshappyanalysisclassification
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7Towards Sentiment Analysis on German Literature
A. Zehe, M. Becker, F. Jannidis, and A. Hotho. Joint German/Austrian Conference on Artificial Intelligence (Künstliche Intelligenz), page 387--394. Springer, (2017)
7 years ago by @becker
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sentiment
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myown
german
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