Zobrazeno 1 - 10
of 389
pro vyhledávání: '"A. Ouzzani"'
Can foundation models (such as ChatGPT) clean your data? In this proposal, we demonstrate that indeed ChatGPT can assist in data cleaning by suggesting corrections for specific cells in a data table (scenario 1). However, ChatGPT may struggle with da
Externí odkaz:
http://arxiv.org/abs/2303.16909
Autor:
Tang, Nan, Fan, Ju, Li, Fangyi, Tu, Jianhong, Du, Xiaoyong, Li, Guoliang, Madden, Sam, Ouzzani, Mourad
Can AI help automate human-easy but computer-hard data preparation tasks that burden data scientists, practitioners, and crowd workers? We answer this question by presenting RPT, a denoising auto-encoder for tuple-to-X models (X could be tuple, token
Externí odkaz:
http://arxiv.org/abs/2012.02469
Publikováno v:
Applied Sciences, Vol 14, Iss 10, p 4067 (2024)
OBJECTIVE: To evaluate the effect of the orthokeratology (OK) lens design, used in the Montreal Experience cohort, on corneal treatment zone characteristics and their relationship to the pupil. METHODS: This retrospective study follows previously pub
Externí odkaz:
https://doaj.org/article/a7cae9d1c0374f0eaddca42b095f4442
Many data problems are solved when the right view of a combination of datasets is identified. Finding such a view is challenging because of the many tables spread across many databases, data lakes, and cloud storage in modern organizations. Finding r
Externí odkaz:
http://arxiv.org/abs/1911.11876
Autor:
Tang, Mingjie, Yu, Yongyang, Aref, Walid G., Mahmood, Ahmed R., Malluhi, Qutaibah M., Ouzzani, Mourad
Due to the ubiquity of spatial data applications and the large amounts of spatial data that these applications generate and process, there is a pressing need for scalable spatial query processing. In this paper, we present new techniques for spatial
Externí odkaz:
http://arxiv.org/abs/1907.03736
Autor:
Sun, Ji, Deng, Dong, Ilyas, Ihab, Li, Guoliang, Madden, Samuel, Ouzzani, Mourad, Stonebraker, Michael, Tang, Nan
An end-to-end data integration system requires human feedback in several phases, including collecting training data for entity matching, debugging the resulting clusters, confirming transformations applied on these clusters for data standardization,
Externí odkaz:
http://arxiv.org/abs/1906.06574
Publikováno v:
In Contact Lens and Anterior Eye February 2023 46(1)
Autor:
Nti, Augustine N., Owusu-Afriyie, Bismark, Osuagwu, Uchechukwu Levi, Kyei, Samuel, Ovenseri-Ogbomo, Godwin, Ogbuehi, Kelechi C., Ouzzani, Mhamed, Agho, Kingsley E., Mashige, Khathutshelo Percy, Ekure, Edgar, Ekpenyong, Bernadine N., Ocansey, Stephen, Ndep, Antor O., Obinwanne, Chukwuemeka Junior, Berntsen, David A., Wolffsohn, James S., Naidoo, Kovin S.
Publikováno v:
In Contact Lens and Anterior Eye February 2023 46(1)
Akademický článek
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Autor:
Thirumuruganathan, Saravanan, Parambath, Shameem A Puthiya, Ouzzani, Mourad, Tang, Nan, Joty, Shafiq
Entity resolution (ER) is one of the fundamental problems in data integration, where machine learning (ML) based classifiers often provide the state-of-the-art results. Considerable human effort goes into feature engineering and training data creatio
Externí odkaz:
http://arxiv.org/abs/1809.11084