Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Li, Xiong"'
Publikováno v:
Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task.
We present an algorithm based on multi-layer transformers for identifying Adverse Drug Reactions (ADR) in social media data. Our model relies on the properties of the problem and the characteristics of contextual word embeddings to extract two views
Publikováno v:
IEEE Trans Knowl Data Eng
In this paper, we study the problem of mining frequent sequences under the rigorous differential privacy model. We explore the possibility of designing a differentially private frequent sequence mining (FSM) algorithm which can achieve both high data
Publikováno v:
IEEE transactions on knowledge and data engineering, vol 30, iss 3
Privacy concern in data sharing especially for health data gains particularly increasing attention nowadays. Now, some patients agree to open their information for research use, which gives rise to a new question of how to effectively use the public
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a66f8b41af0d2c682097b417435a2b42
https://escholarship.org/uc/item/3dn265b1
https://escholarship.org/uc/item/3dn265b1
Autor:
Luca Bonomi, Li Xiong
Publikováno v:
Proceedings of the VLDB Endowment. 6:1422-1427
The mining of frequent patterns is a fundamental component in many data mining tasks. A considerable amount of research on this problem has led to a wide series of efficient and scalable algorithms for mining frequent patterns. However, releasing the
Publikováno v:
Advanced Data Mining and Applications ISBN: 9783319495859
ADMA
ADMA
The world city network (WCN) research has been promoting the evaluation algorithms in complex networks. The study of urban network focuses on the measurements of city position in the WCN. In previous study, a set of algorithms such as centricity eval
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ee200066fc267573519e7f5dc697d767
https://doi.org/10.1007/978-3-319-49586-6_53
https://doi.org/10.1007/978-3-319-49586-6_53
Publikováno v:
CIKM
Skyline is a set of points that are not dominated by any other point. Given uncertain objects, probabilistic skyline has been studied which computes objects with high probability of being skyline. While useful for selecting individual objects, it is
Publikováno v:
Advances in Knowledge Discovery and Data Mining ISBN: 9783319066073
PAKDD (1)
PAKDD (1)
The pervasive usage of LBS (Location Based Services) has caused serious risk of personal privacy. In order to preserve the privacy of locations, only the anonymized or perturbated data are published. At the same time, the data mining results for the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::47dd33c8ed33dd9b239eb5d7f9614517
https://doi.org/10.1007/978-3-319-06608-0_49
https://doi.org/10.1007/978-3-319-06608-0_49
Publikováno v:
SIGMOD Conference
Sharing aggregate statistics of private data can be of great value when data mining can be performed in real-time to understand important phenomena such as influenza outbreaks or traffic congestion. However, to this date there have been no tools for
Publikováno v:
WWW
We study the problem of anonymizing user profiles so that user privacy is sufficiently protected while the anonymized profiles are still effective in enabling personalized web search. We propose a Bayes-optimal privacy notion to bound the prior and p
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783642155451
Secure Data Management
Secure Data Management
Differential privacy is a strong notion for protecting individual privacy in privacy preserving data analysis or publishing. In this paper, we study the problem of differentially private histogram release based on an interactive differential privacy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bcdbc54c6387a4e44f83f1b9620d8c14
https://doi.org/10.1007/978-3-642-15546-8_11
https://doi.org/10.1007/978-3-642-15546-8_11