Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Françoise Fessant"'
Publikováno v:
Communications in Computer and Information Science ISBN: 9783030937355
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dec409eb42c096cff2a2610c0a9659a0
https://doi.org/10.1007/978-3-030-93736-2_10
https://doi.org/10.1007/978-3-030-93736-2_10
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319644677
DEXA (1)
28th International Conference on Database and Expert Systems Applications (DEXA 2017)
28th International Conference on Database and Expert Systems Applications (DEXA 2017), Aug 2017, Lyon, France. pp.345-351, ⟨10.1007/978-3-319-64468-4_26⟩
DEXA (1)
28th International Conference on Database and Expert Systems Applications (DEXA 2017)
28th International Conference on Database and Expert Systems Applications (DEXA 2017), Aug 2017, Lyon, France. pp.345-351, ⟨10.1007/978-3-319-64468-4_26⟩
We propose a methodology to anonymize microdata (i.e. a table of n individuals described by d attributes). The goal is to be able to release an anonymized data table built from the original data that protects against the re-identification risk. The p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f236ac6b56ea2a6a6c5ee36c7fcc9289
https://doi.org/10.1007/978-3-319-64468-4_26
https://doi.org/10.1007/978-3-319-64468-4_26
Publikováno v:
Personal Analytics and Privacy. An Individual and Collective Perspective ISBN: 9783319719696
PAP@PKDD/ECML
Personal Analytics and Privacy. An Individual and Collective Perspective
Personal Analytics and Privacy. An Individual and Collective Perspective, 2017
PAP@PKDD/ECML
Personal Analytics and Privacy. An Individual and Collective Perspective
Personal Analytics and Privacy. An Individual and Collective Perspective, 2017
International audience; We propose a methodology to anonymize microdata (i.e. a table of n individuals described by d attributes). The goal is to be able to release an anonymized data table built from the original data while meeting the differential
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d403a4524ec7e3825fd8eb837a715146
https://doi.org/10.1007/978-3-319-71970-2_5
https://doi.org/10.1007/978-3-319-71970-2_5
Publikováno v:
Annales Des Télécommunications. 62:350-368
The very rapid adoption of new applications by some segments of the adsl customers may have a strong impact on the quality of service delivered to all customers. This makes the segmentation of adsl customers according to their network usage a critica
Autor:
Françoise Fessant, Sophie Midenet
Publikováno v:
Neural Computing & Applications. 10:300-310
This paper is dedicated to erroneous data detection and imputation methods in surveys. We describe experiments conducted under the scope of a European project for studying new statistical methods based on neural networks. We show that the selforganis
Publikováno v:
Ecological Modelling. 120:141-156
Artificial neural networks (ANNs) are applied as a new type of model to estimate the daily pH of the Middle Loire river. The model is used for pH measurement screening, error detection (abnormal values, discontinuities and recording drifts) and valid
Publikováno v:
Solar Physics. 168:423-433
In this paper we propose a comparison between two methods for the problem of long-term prediction of the smoothed sunspot index. These two methods are first the classical method of McNish and Lincoln (as improved by Stewart and Ostrow), and second a
Publikováno v:
Neural Processing Letters. 3:101-106
Recently, a lot of papers have been published in the field of time series prediction using connectionist models. Nevertheless we think that one of the major problem with is rarely treated in the literature is related to the choice of input parameters
In this chapter, the authors describe Reperio, a flexible and generic industrial recommender system able to deal with several kinds of data sources (content-based, collaborative, social network) in the same framework and to work on multi-platforms (W
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c27f97bb6a3ba38427ca168a11378b57
https://doi.org/10.4018/978-1-4666-2542-6.ch004
https://doi.org/10.4018/978-1-4666-2542-6.ch004
Autor:
Franck Meyer, Françoise Fessant
Publikováno v:
Web Intelligence
We describe Reperio, a flexible and generic industrial recommender system able to deal with several kinds of data sources (content-based, collaborative, social network...) into the same framework and to work on multi platforms (web service in a multi