Zobrazeno 1 - 10
of 67
pro vyhledávání: '"Irina Trubitsyna"'
Autor:
Reza Shahbazian, Irina Trubitsyna
Publikováno v:
IEEE Access, Vol 11, Pp 40878-40904 (2023)
Applications for human sensing, also known as (human) occupancy detection, include energy management systems for intelligent buildings, intruder detection, e-health systems, the identification of everyday activity, and the monitoring of vital signs.
Externí odkaz:
https://doaj.org/article/041855ebfab9427986a76c875dd02c65
Publikováno v:
Intelligent Systems with Applications, Vol 17, Iss , Pp 200146- (2023)
Several medical applications deal with inconsistent knowledge bases, namely information that possibly violates given constraints, as they may not be enforced or satisfied. For instance, inconsistency may arise in clinical data integration, where mult
Externí odkaz:
https://doaj.org/article/e80e572fc5e44775ae7e485907a5dfc0
Autor:
Reza Shahbazian, Irina Trubitsyna
Publikováno v:
Information, Vol 13, Iss 12, p 575 (2022)
Insights and analysis are only as good as the available data. Data cleaning is one of the most important steps to create quality data decision making. Machine learning (ML) helps deal with data quickly, and to create error-free or limited-error datas
Externí odkaz:
https://doaj.org/article/0a2e2a726765454380effc1b9ada05e7
Autor:
Enrico Bazzi, Nunziato Cassavia, Davide Chiggiato, Elio Masciari, Domenico Saccà, Alessandra Spada, Irina Trubitsyna
Publikováno v:
Information, Vol 9, Iss 12, p 303 (2018)
Big Data, as a new paradigm, has forced both researchers and industries to rethink data management techniques which has become inadequate in many contexts. Indeed, we deal everyday with huge amounts of collected data about user suggestions and search
Externí odkaz:
https://doaj.org/article/049914ad9836409798b92659f6be74e6
Publikováno v:
Information Sciences. 625:757-779
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::962797ec76ccae9231bf09fd78315c08
https://doi.org/10.1016/j.ins.2022.12.116
https://doi.org/10.1016/j.ins.2022.12.116
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 36:5451-5460
Dung’s Argumentation Framework (AF) has been extended in several directions, including the possibility of representing unquantified uncertainty about the existence of arguments and attacks. The framework resulting from such an extension is called i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::abc8f73f945fd2955c93bcc7838b9f0c
https://doi.org/10.1609/aaai.v36i5.20483
https://doi.org/10.1609/aaai.v36i5.20483
Publikováno v:
Scopus-Elsevier
KR
KR
Query answering over inconsistent knowledge bases is a problem that has attracted a great deal of interest over the years. Different inconsistency-tolerant semantics have been proposed, and most of them are based on the notion of repair, that is, a "
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::317eaa5ae7c3de81c8db58c9d5c911b8
https://hdl.handle.net/2434/946600
https://hdl.handle.net/2434/946600
Publikováno v:
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence.
Dung's abstract Argumentation Framework (AF) has emerged as a central formalism for argumentation in AI. Preferences in AF allow to represent the comparative strength of arguments in a simple yet expressive way. In this paper we first investigate the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1d1069529443369da11038490b360b7a
https://doi.org/10.24963/ijcai.2022/349
https://doi.org/10.24963/ijcai.2022/349
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 35:6175-6184
Dung's abstract Argumentation Framework (AF) has emerged as a central formalism in formal argumentation. Key aspects of the success and popularity of Dung's framework include its simplicity and expressiveness. Integrity constraints help to express do
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::297ebb444ec3c883657846112741fc7c
https://doi.org/10.1609/aaai.v35i7.16768
https://doi.org/10.1609/aaai.v35i7.16768