Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Alice Marascu"'
Autor:
Ulf Brefeld, Edward Curry, Alice Marascu, Neil Hurley, Michele Berlingerio, Brian MacNamee, Elizabeth M. Daly, Fabio Pinelli
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030109967
Brefeld, U, Curry, E, Daly, E, MacNamee, B, Marascu, A, Pinelli, F, Berlingerio, M & Hurley, N (eds) 2019, Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018, Proceedings-Part III . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11054 LNAI, vol. 11053, Springer, Cham . https://doi.org/10.1007/978-3-030-10997-4
Brefeld, U, Curry, E, Daly, E, MacNamee, B, Marascu, A, Pinelli, F, Berlingerio, M & Hurley, N (eds) 2019, Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018, Proceedings-Part III . Lecture Notes in Computer Science, vol. 11053, vol. 11053, Springer, Cham . DOI: 10.1007/978-3-030-10997-4
Brefeld, U, Curry, E, Daly, E, MacNamee, B, Marascu, A, Pinelli, F, Berlingerio, M & Hurley, N (eds) 2019, Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018, Proceedings-Part III . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11054 LNAI, vol. 11053, Springer, Cham . https://doi.org/10.1007/978-3-030-10997-4
Brefeld, U, Curry, E, Daly, E, MacNamee, B, Marascu, A, Pinelli, F, Berlingerio, M & Hurley, N (eds) 2019, Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018, Proceedings-Part III . Lecture Notes in Computer Science, vol. 11053, vol. 11053, Springer, Cham . DOI: 10.1007/978-3-030-10997-4
The three volume proceedings LNAI 11051 – 11053 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, held in Dublin, Ireland, in September 2018. The total of 131 r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::03b9df4b3b2e88ceb7755478a48f2f99
https://doi.org/10.1007/978-3-030-10997-4
https://doi.org/10.1007/978-3-030-10997-4
Autor:
Davide Mottin, Themis Palpanas, Senjuti Basu Roy, Yannis Velegrakis, Gautam Das, Alice Marascu
Publikováno v:
The VLDB Journal. 25:597-622
We propose a principled optimization-based interactive query relaxation framework for queries that return no answers. Given an initial query that returns an empty-answer set, our framework dynamically computes and suggests alternative queries with fe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0dc12a591b0e31fa8ed841ed8169f8f0
https://doi.org/10.1007/s00778-016-0431-8
https://doi.org/10.1007/s00778-016-0431-8
Autor:
Themis Palpanas, Gautam Das, Yannis Velegrakis, Senjuti Basu Roy, Davide Mottin, Alice Marascu
Publikováno v:
Mottin, D, Marascu, A, Basu Roy, S, Das, G, Palpanas, T & Velegrakis, Y 2013, ' A Probabilistic Optimization Framework for the Empty-Answer Problem ' PVLDB, bind 6, nr. 14 .
Scopus-Elsevier
Scopus-Elsevier
We propose a principled optimization-based interactive query relaxation framework for queries that return no answers. Given an initial query that returns an empty answer set, our framework dynamically computes and suggests alternative queries with le
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dd42dcd6ecf3b81b1b8edd8b5481f291
https://doi.org/10.14778/2556549.2556560
https://doi.org/10.14778/2556549.2556560
Autor:
Eric Bouillet, Olivier Verscheure, Alice Marascu, Pascal Pompey, Philippe Cudré-Mauroux, Martin Grund, Michael Wurst
Publikováno v:
BigData Conference
Large-scale critical infrastructures such as transportation, energy, or water distribution networks are increasingly equipped with smart sensor technologies. Low-latency analytics on the resulting times series would open the door to many exciting opp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::975ee09ece0ed67c6f83ea4306131c93
https://doi.org/10.1109/bigdata.2014.7004244
https://doi.org/10.1109/bigdata.2014.7004244
Autor:
Senjuti Basu Roy, Gautam Das, Themis Palpanas, Alice Marascu, Yannis Velegrakis, Davide Mottin
Publikováno v:
SIGMOD Conference
We present IQR, a system that demonstrates optimization based interactive relaxations for queries that return an empty answer. Given an empty answer, IQR dynamically suggests one relaxation of the original query conditions at a time to the user, base
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9b99867982806bd696823d3ed72e1721
https://doi.org/10.1145/2588555.2594512
https://doi.org/10.1145/2588555.2594512
Autor:
Philippe Cudré-Mauroux, Martin Grund, Eric Bouillet, Alice Marascu, Pascal Pompey, Michael Wurst, Olivier Verscheure
Publikováno v:
BigData Conference
Smart sensors are increasingly being used to manage and monitor critical urban infrastructures, e.g., for telecommunication, transport, water, or energy networks, as well as for healthcare or smart buildings. Sensor-based monitoring systems offer way
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5d589db870206738977260e7dd642386
https://doi.org/10.1109/bigdata.2013.6691772
https://doi.org/10.1109/bigdata.2013.6691772
Publikováno v:
Advances in Knowledge Discovery and Data Mining ISBN: 9783642302190
PAKDD (2)
PAKDD (2)
Nowadays online monitoring of data streams is essential in many real life applications, like sensor network monitoring, manufacturing process control, and video surveillance. One major problem in this area is the online identification of streaming se
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9a48deb492fe2a4791711d70d24887a4
https://doi.org/10.1007/978-3-642-30220-6_19
https://doi.org/10.1007/978-3-642-30220-6_19
Autor:
Alice Marascu, Florent Masseglia
Publikováno v:
Intelligent Data Analysis
Intelligent Data Analysis, IOS Press, 2011, 15 (1), pp.89-105. ⟨10.3233/IDA-2010-0457⟩
Intelligent Data Analysis, 2011, 15 (1), pp.89-105. ⟨10.3233/IDA-2010-0457⟩
Intelligent Data Analysis, IOS Press, 2011, 15 (1), pp.89-105. ⟨10.3233/IDA-2010-0457⟩
Intelligent Data Analysis, 2011, 15 (1), pp.89-105. ⟨10.3233/IDA-2010-0457⟩
International audience; Outlyingness is a subjective concept relying on the isolation level of a (set of) record(s). Clustering-based outlier detection is a field that aims to cluster data and to detect outliers depending on their characteristics (i.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e30e3c94301ff345d6189eb51f744a1c
https://hal.inria.fr/hal-00789034
https://hal.inria.fr/hal-00789034
Publikováno v:
ACM Symposium on Applied Computing
ACM Symposium on Applied Computing, Mar 2010, Sierre, Switzerland
SAC
ACM Symposium on Applied Computing, Mar 2010, Sierre, Switzerland
SAC
Summarizing a set of streaming time series is an important issue that reliably allows information to be monitored and stored in domains such as finance [12], networks [2, 1], etc. To date, most of existing algorithms have focused on this problem by s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7d73cef799e6a0320b4d6ab43ff3ed2a
https://inria.hal.science/inria-00461781
https://inria.hal.science/inria-00461781
Publikováno v:
Advances in Knowledge Discovery and Management
Fabrice Guillet; Gilbert Ritschard; Djamel Abdelkader Zighed; Henri Briand. Advances in Knowledge Discovery and Management, 292, Springer, pp.217-234, 2010, Studies in Computational Intelligence, 978-3-642-00579-4. ⟨10.1007/978-3-642-00580-0_13⟩
Advances in Knowledge Discovery and Management ISBN: 9783642005794
EGC (best of volume)
Fabrice Guillet; Gilbert Ritschard; Djamel Abdelkader Zighed; Henri Briand. Advances in Knowledge Discovery and Management, 292, Springer, pp.217-234, 2010, Studies in Computational Intelligence, 978-3-642-00579-4. ⟨10.1007/978-3-642-00580-0_13⟩
Advances in Knowledge Discovery and Management ISBN: 9783642005794
EGC (best of volume)
International audience; Data mining for intrusion detection can be divided into several sub-topics, among which unsupervised clustering (which has controversial properties). Unsupervised clustering for intrusion detection aims to i) group behaviours
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4d25b0a41ea350720e648f9641273490
https://hal-lirmm.ccsd.cnrs.fr/lirmm-00798705/document
https://hal-lirmm.ccsd.cnrs.fr/lirmm-00798705/document