Zobrazeno 1 - 10
of 64
pro vyhledávání: '"Yuni Xia"'
Publikováno v:
Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 2.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::559deb6f7679c926fb99ad3980d7085d
https://doi.org/10.1145/3545947.3576237
https://doi.org/10.1145/3545947.3576237
Publikováno v:
Knowledge and Information Systems. 51:821-850
Temporally uncertain data widely exist in many real-world applications. Temporal uncertainty can be caused by various reasons such as conflicting or missing event timestamps, network latency, granularity mismatch, synchronization problems, device pre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::431a66b0780f6904758ca33ea4ba5ed2
https://doi.org/10.1007/s10115-016-0977-1
https://doi.org/10.1007/s10115-016-0977-1
Publikováno v:
Knowledge and Information Systems. 53:637-670
Research on recommendation systems has gained a considerable amount of attention over the past decade as the number of online users and online contents continue to grow at an exponential rate. With the evolution of the social web, people generate and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1256bd18c3ae65e5c59dd14f166d0333
https://doi.org/10.1007/s10115-016-0967-3
https://doi.org/10.1007/s10115-016-0967-3
Publikováno v:
Journal of Intelligent & Fuzzy Systems. 25:1067-1083
Real world applications as sensor networks and RFID networks usually generate data with uncertainty. Data uncertainty comes from many sources, as measurement errors, limited precision, data aggregation and so on. Classical data mining applications ne
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3c44dd73368b8612294140bc8f5d461a
https://doi.org/10.3233/ifs-130794
https://doi.org/10.3233/ifs-130794
Publikováno v:
CIKM
Due to the continuous, unbounded, and dynamic characteristics of the streaming data, mining data streams becomes a very challenging task. When analyzing online data streams, it is necessary to produce accurate results in a very short amount of time.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d723d7685cc0aa6f2afdf18089a985cb
https://doi.org/10.1145/2983323.2983341
https://doi.org/10.1145/2983323.2983341
Autor:
Suranga N. Kasthurirathne, Shaun J. Grannis, Huiping Xu, Brian E. Dixon, Burke W. Mamlin, Yuni Xia, Judy Wawira Gichoya
Publikováno v:
Journal of biomedical informatics. 69
Objectives Existing approaches to derive decision models from plaintext clinical data frequently depend on medical dictionaries as the sources of potential features. Prior research suggests that decision models developed using non-dictionary based fe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1b1b34396f07b6b32c7f13ffc51eb586
https://pubmed.ncbi.nlm.nih.gov/28410983
https://pubmed.ncbi.nlm.nih.gov/28410983
Publikováno v:
IPDPS
Outlier detection or anomaly detection is applied in numerous applications, such as fraud detection, network intrusion detection, manufacturing, and environmental monitoring. Due to the continuous and dynamic characteristics of streaming data, outlie
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::18674189d8065869f5b36a03276a1540
https://doi.org/10.1109/ipdps.2016.101
https://doi.org/10.1109/ipdps.2016.101
Publikováno v:
Advances in Knowledge Discovery and Data Mining ISBN: 9783319317496
PAKDD (2)
PAKDD (2)
While sequential pattern mining SPM is an import application in uncertain databases, it is challenging in efficiency and scalability. In this paper, we develop a dynamic programming DP approach to mine probabilistic frequent sequential patterns in di
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::654dc8bc557a905332f914be5cbba807
https://doi.org/10.1007/978-3-319-31750-2_2
https://doi.org/10.1007/978-3-319-31750-2_2
Autor:
Shenhui Jiang, Shiaofen Fang, Shaun J. Grannis, Jeremy Keiper, Mathew J. Palakal, Yuni Xia, Sam Bloomquist
Publikováno v:
VISIGRAPP (2: IVAPP)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fcc6dfbeb2781f06513b9b758f53deac
https://doi.org/10.5220/0005714002120219
https://doi.org/10.5220/0005714002120219
Publikováno v:
Knowledge and Information Systems. 37:219-244
Data uncertainty is inherent in many real-world applications such as sensor monitoring systems, location-based services, and medical diagnostic systems. Moreover, many real-world applications are now capable of producing continuous, unbounded data st
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e4d63dd628da649033c563aa68bcc642
https://doi.org/10.1007/s10115-012-0581-y
https://doi.org/10.1007/s10115-012-0581-y