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RecB: Set Theory based Technique for Large Scale Pattern Mining in Web Logs
2015
International Journal of Computer Applications
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This paper stresses the importance of data preprocessing and introduces an efficient method for mining patterns in large sized collections of web logs (of all types) based on classic set theory properties ...
Another challenge is that many proposed pattern mining techniques are usually tested on small benchmark datasets, so their performance on a large scale is hard to predict. ...
This paper describes some properties of set theory applied to web usage mining and offers a method for pattern identification in weblog data. ...
doi:10.5120/ijca2015905584
fatcat:z6hmy6wkmvamnkalxh7n324sbq
A Parameter-Free Classification Method for Large Scale Learning
2009
Journal of machine learning research
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We finally report results on the Large Scale Learning challenge, where our method obtains state of the art performance within practicable computation time. ...
In this paper, we present a parameter-free scalable classification method, which is a step towards fully automatic data mining. ...
I would also like to thank the organizers of the Large Scale Learning Challenge for their valuable initiative. ...
dblp:journals/jmlr/Boulle09
fatcat:3owpvud6uzd2bh44ns7cluymdi
A Method for Detecting Large-scale Network Anomaly Behavior
2018
ITM Web of Conferences
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However, due to the rapid expansion of the network scale, various newly and large-scale attacking methods are endless, and it has obvious defects in flexibility, adaptability and so on. ...
A clustering model identification method based on the statistics has been proposed to improve the ability to detect scale anomaly behavior of the traditional anomaly detection technology. ...
In order to solve the problem that the improved algorithm is not effective for large-scale abnormal behavior detection, this paper proposes a clustering model identification pattern method, which combines ...
doi:10.1051/itmconf/20181701012
fatcat:yjjei5rbz5gg3ffk33e7flm46i
A Simple Method for Detecting Interactions between a Treatment and a Large Number of Covariates
[article]
2012
arXiv
pre-print
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The modified data can be used for other purposes, for example large scale hypothesis testing for determining which of a set of covariates interact with a treatment variable. ...
We consider a setting in which we have a treatment and a large number of covariates for a set of observations, and wish to model their relationship with an outcome of interest. ...
We also can do large scale hypothesis testing on the modified data to determine which gene-treatment interactions have a significant effect on the outcome. ...
arXiv:1212.2995v1
fatcat:b5zbrctnszddhkjcktk2qsx6cq
A Proactive Complex Event Processing Method for Large-Scale Transportation Internet of Things
2014
International Journal of Distributed Sensor Networks
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In this paper, a proactive complex event processing method is proposed for large-scale transportation IoT. ...
The experimental evaluations show that this method can support proactive complex event processing well in large-scale transportation Internet of Things. ...
Acknowledgments This work is supported by the National Natural Science Foundation of China (no. 61371116) and the Hunan Provincial Natural Science Foundation (no. 13JJ3046). ...
doi:10.1155/2014/159052
fatcat:kj5hwjolqjh2lbbctlf45nr4uy
Large-plate method for the assay of neomycin in serum
1969
Applied microbiology
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A large-plate method employing radial diffusion from small paper discs for assaying serum levels of neomycin is described. ...
The large-plate method is considered to be more efficient than the use of the smaller petri dishes. ...
The large-plate method is the method of choice for a greater number of assays. ...
pmid:4906999
pmcid:PMC377983
fatcat:kxo6g5qh65dl5p6xkqsauxkhum
Analyzing large-scale human mobility data: a survey of machine learning methods and applications
2018
Knowledge and Information Systems
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The efforts to mine significant patterns within large-scale, high-dimensional mobility data have solicited use of advanced analysis techniques, usually based on machine learning methods, and therefore, ...
We categorize these approaches and models in a taxonomy based on their positioning characteristics, the scale of analysis, the properties of the modeling approach, and the class of applications they can ...
Acknowledgements This work is supported by the Israeli Ministry of Science, Technology, and Space, Grant No. 3-8709: Learning and mining mobility patterns using stochastic models. ...
doi:10.1007/s10115-018-1186-x
fatcat:nesak2c3uzhyvhynd5gv4vmeve
Large-Plate Method for the Assay of Neomycin in Serum
1969
Applied microbiology
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The large-plate method is the method of choice for a greater number of assays. ...
A large-plate method employing radial diffusion from small paper discs for assaying serum levels of neomycin is described. ...
The large-plate method is the method of choice for a greater number of assays. ...
doi:10.1128/aem.18.3.350-354.1969
fatcat:fjayr5di4vgdhgsygiwxa4o774
NC-link: A New Linkage Method for Efficient Hierarchical Clustering of Large-Scale Data
2017
IEEE Access
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To verify our proposal, we thoroughly tested it with a number of large-scale real and synthetic data sets. ...
To address large-scale data, various approximate/parallel algorithms have been proposed to reduce the computational cost of HC. ...
For in-memory processing of large-scale data, it is crucial for a mining algorithm to have linear space complexity. ...
doi:10.1109/access.2017.2690987
fatcat:yurib2tb7jhy7mo44mi72try2a
Disease types discovery from a large database of inpatient records: A sepsis study
2016
Methods
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In the method described in this paper, we map a very large EHR database containing more than a million inpatient cases into a low dimensional space where diseases with similar phenotypes have similar representation ...
For instance, sepsis, a systemic and progressive inflammation, can be caused by many factors, and can have multiple manifestations on different human organs. ...
Large-scale efforts for generating and sharing phenotypes were established recently [13, 14] . ...
doi:10.1016/j.ymeth.2016.07.021
pmid:27477211
fatcat:f3x5ozi6bfctnezkboh3kao5cu
A Network Inference Method for Large-Scale Unsupervised Identification of Novel Drug-Drug Interactions
2013
PLoS Computational Biology
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We show that our method is able to accurately predict interactions, both in exhaustive pairwise interaction data between small sets of drugs, and in large-scale databases. ...
Here we present a network inference algorithm to predict uncharacterized drug-drug interactions. ...
A recent large-scale study of older adults (ages 57-85) in the U.S. found that 29% of them use five or more prescription medications concurrently, and that as many as 4% may be at risk of having a major ...
doi:10.1371/journal.pcbi.1003374
pmid:24339767
pmcid:PMC3854677
fatcat:avezwhvxong33jhcrv77oa5pjq
A Simple Method for Estimating Interactions Between a Treatment and a Large Number of Covariates
2014
Journal of the American Statistical Association
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We consider a setting in which we have a treatment and a potentially large number of covariates for a set of observations, and wish to model their relationship with an outcome of interest. ...
It can be useful for practicing personalized medicine: determining from a large set of biomarkers the subset of * ...
The modified covariates idea can be used for other purposes, for example, large scale hypothesis testing for determining which of a set of covariates interact with a treatment variable. ...
doi:10.1080/01621459.2014.951443
pmid:25729117
pmcid:PMC4338439
fatcat:e23vk4wdj5hevi4odtujmkgp5y
A fuzzy neighborhood rough set method for anomaly detection in large scale data
2020
IAES International Journal of Artificial Intelligence (IJ-AI)
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However, the existing outlier detection algorithms suffer the drawbacks that they are inefficient in dealing with large scale datasets. ...
Mining Outlier in database is to find exceptional objects that deviate from the rest of the datasets. ...
ACKNOWLEDGEMENTS The authors are very much thankful to the unanimous reviewers of the paper and editors of the journal for their constructive and helpful comments that improved the quality of the paper ...
doi:10.11591/ijai.v9.i1.pp1-10
fatcat:5ueczwvckvgufh4sgc7foeapfy
A fish-based index of large river quality for French Guiana (South America): method and preliminary results
2006
Aquatic Living Resources
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The method was developed from 53 samples of 27 reaches in 7 hydrographic basins of French Guiana. ...
La méthode a été développée à partir de 53 échantillons réalisés sur 27 sites de 7 bassins hydrographiques de Guyane française. ...
The first author received a grant from IRD (Grant 32801A). ...
doi:10.1051/alr:2006003
fatcat:qykcbz2osvh35jt7wf5gugm7oe
Characterizing large-scale glaciotectonic sediment deformation using electrical resistivity methods
2016
Journal of Geophysics and Engineering
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Large-scale sediment deformation structures formed by glaciotectonic processes have been identified south of Ludington, Michigan. ...
Throughout the area, the surface topography and locations of springs indicate a complicated subsurface structure and a preferred pattern of groundwater drainage. ...
CONCLUSIONS This paper presents one of the first investigations of large-scale glaciotectonic deformation using electrical resistivity methods. ...
doi:10.1088/1742-2132/13/2/s39
fatcat:gcw3xr3eerbrhem5uejbn5rdsm
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