Zobrazeno 1 - 10
of 173
pro vyhledávání: '"Kjetil Nørvåg"'
Publikováno v:
ACM Transactions on Knowledge Discovery from Data
Dense subregion (subgraph & subtensor) detection is a well-studied area, with a wide range of applications, and numerous efficient approaches and algorithms have been proposed. Approximation approaches are commonly used for detecting dense subregions
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::084bf5b21d5cde25b42071af2b61c14c
https://doi.org/10.1145/3446668
https://doi.org/10.1145/3446668
Publikováno v:
SIGIR Forum
The 44th European Conference on Information Retrieval (ECIR'22) was held in Stavanger, Norway. It represents a landmark, not only for being the northernmost ECIR ever, but also for being the first major IR conference in a hybrid format. This article
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f343f3b44a96c06f4769092dbac7dbc6
https://hdl.handle.net/11250/3061987
https://hdl.handle.net/11250/3061987
Publikováno v:
Big Data Analytics and Knowledge Discovery ISBN: 9783031126697
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9c8745107dfed3e4ff937fd778fbd7c4
https://doi.org/10.1007/978-3-031-12670-3_6
https://doi.org/10.1007/978-3-031-12670-3_6
Publikováno v:
Information Processing & Management. 56:1280-1299
While geographical metadata referring to the originating locations of tweets provides valuable information to perform effective spatial analysis in social networks, scarcity of such geotagged tweets imposes limitations on their usability. In this wor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::632ccdef97b94c1c3c74f33dbdaf30f9
https://doi.org/10.1016/j.ipm.2019.02.013
https://doi.org/10.1016/j.ipm.2019.02.013
Publikováno v:
Knowledge-Based Systems. 165:13-29
The set of closed high-utility itemsets (CHUIs) concisely represents the exact utility of all itemsets. Yet, it can be several orders of magnitude smaller than the set of all high-utility itemsets. Existing CHUI mining algorithms assume that database
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8ecb56beb0c7baf3327cd91fb0705f4d
https://doi.org/10.1016/j.knosys.2018.11.019
https://doi.org/10.1016/j.knosys.2018.11.019
Publikováno v:
ACM Transactions on Management Information Systems (TMIS)
This article introduces a highly efficient pattern mining technique called Clustering-based Pattern Mining (CBPM). This technique discovers relevant patterns by studying the correlation between transactions in the transaction database based on cluste
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::14d8ee87977597a73d5df4bd91d5f723
https://hdl.handle.net/11250/2760860
https://hdl.handle.net/11250/2760860
Autor:
Asma Belhadi, Youcef Djenouri, Kjetil Nørvåg, Florent Masseglia, Heri Ramampiaro, Jerry Chun-Wei Lin
Publikováno v:
Engineering Applications of Artificial Intelligence
Engineering Applications of Artificial Intelligence, 2020, 95, pp.#103857. ⟨10.1016/j.engappai.2020.103857⟩
Engineering Applications of Artificial Intelligence, Elsevier, 2020, 95, pp.#103857. ⟨10.1016/j.engappai.2020.103857⟩
Engineering Applications of Artificial Intelligence, 2020, 95, pp.#103857. ⟨10.1016/j.engappai.2020.103857⟩
Engineering Applications of Artificial Intelligence, Elsevier, 2020, 95, pp.#103857. ⟨10.1016/j.engappai.2020.103857⟩
International audience; This paper provides a short overview of space time series clustering, which can be generally grouped into three main categories such as: hierarchical, partitioning-based, and overlapping clustering. The first hierarchical cate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2e78afe3753a4d9c4746d458295c2e89
https://hal-lirmm.ccsd.cnrs.fr/lirmm-03036868/document
https://hal-lirmm.ccsd.cnrs.fr/lirmm-03036868/document
Publikováno v:
ICDE
Dense subtensor detection is a well-studied area, with a wide range of applications, and numerous efficient approaches and algorithms have been proposed. Existing algorithms are generally efficient for dense subtensor detection and could perform well
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4584cef9e3e3364e0c933ad84646b409
https://doi.org/10.1109/icde48307.2020.00061
https://doi.org/10.1109/icde48307.2020.00061
Publikováno v:
CIKM
By "checking into'' various points-of-interest (POIs), users create a rich source of location-based social network data that can be used in expressive spatio-social queries. This paper studies the use of popularity as a means to diversify results of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::64df555767f9019e9a5ff263e300e3ca
https://hdl.handle.net/11250/2758066
https://hdl.handle.net/11250/2758066
Autor:
Akrivi Vlachou, Nikolaos Koutroumanis, Dimitris Poulopoulos, Christos Doulkeridis, Kjetil Nørvåg
Publikováno v:
PCI
This paper presents the research activities in the context of the SPADES project for scalable indexing and processing of big spatial and spatio-textual data. Management of spatio-textual data raises challenges due to the high dimensional nature of te
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f63606770b2e3a4be566056fc44aaaf6
https://hdl.handle.net/11250/2732376
https://hdl.handle.net/11250/2732376