Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Jung-Yi Jiang"'
Publikováno v:
IEEE Access, Vol 9, Pp 133650-133662 (2021)
Many object re-identification (Re-ID) methods that depend on large-scale training datasets have been proposed in recent years. However, the performance of these methods degrades dramatically when insufficient training data are available. To address t
Externí odkaz:
https://doaj.org/article/8cfd7f4a7c3642fe9cb3802618408ccd
Autor:
Jung-Yi Jiang, 江忠益
99
This thesis proposes some novel approaches for feature reduction and multi-label classification for text datasets. In text processing, the bag-of-words model is commonly used, with each document modeled as a vector in a high dimensional space
This thesis proposes some novel approaches for feature reduction and multi-label classification for text datasets. In text processing, the bag-of-words model is commonly used, with each document modeled as a vector in a high dimensional space
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/14966935309991951355
Autor:
Jung-Yi Jiang, 江忠益
92
There are two main contributions in the thesis. Firstly, we design a novel and efficient algorithm for mining calendar-based association rules which have multilevel time granularities in temporal databases. Unlike apriori-like approaches, ou
There are two main contributions in the thesis. Firstly, we design a novel and efficient algorithm for mining calendar-based association rules which have multilevel time granularities in temporal databases. Unlike apriori-like approaches, ou
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/15144645200000630746
Autor:
Shie-Jue Lee, Jung-Yi Jiang
Publikováno v:
IEEE Transactions on Fuzzy Systems. 22:1457-1471
We propose a fuzzy based method for multilabel text classification in which a document can belong to one or more than one category. In text categorization, the number of the involved features is usually huge, causing the curse of the dimensionality p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::718af5c04344ce93c4e9d4dd16c4f85b
https://doi.org/10.1109/tfuzz.2013.2294355
https://doi.org/10.1109/tfuzz.2013.2294355
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 26:1575-1590
Measuring the similarity between documents is an important operation in the text processing field. In this paper, a new similarity measure is proposed. To compute the similarity between two documents with respect to a feature, the proposed measure ta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4e28f258e8808d35b29f125c6c3c1f44
https://doi.org/10.1109/tkde.2013.19
https://doi.org/10.1109/tkde.2013.19
Publikováno v:
ICUFN
This paper present a Data Dissemination strategy based on Time Validity (DDTV) to deal with time-sensitive contents in opportunistic networks. Time sensitivity refers to the constraint that the content must be delivered to the destinations within a g
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c762f8b020f74518af3a105120327b3c
https://doi.org/10.1109/icufn.2016.7536956
https://doi.org/10.1109/icufn.2016.7536956
Autor:
Van-Oanh Sai, Jung-Yi Jiang, Trong-The Nguyen, Quang-Duy Le, Mong-Fong Horng, Yuh-Chung Lin, Chin-Shiuh Shieh
Publikováno v:
CMCSN
In engineering and design problems, various noisy non-linear mathematical optimization problems can't be efficaciously solved by using conventional optimization techniques. But metaheuristic algorithms seem very efficient to approach in these problem
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::225a21746f92b36730565d0cd9fe0c51
https://doi.org/10.1109/cmcsn.2016.29
https://doi.org/10.1109/cmcsn.2016.29
Publikováno v:
Expert Systems with Applications. 39:2813-2821
We propose an efficient approach, FSKNN, which employs fuzzy similarity measure (FSM) and k nearest neighbors (KNN), for multi-label text classification. One of the problems associated with KNN-like approaches is its demanding computational cost in f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5a4ce1501f6f1bcaebdfc1fff3e30680
https://doi.org/10.1016/j.eswa.2011.08.141
https://doi.org/10.1016/j.eswa.2011.08.141
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 23:335-349
Feature clustering is a powerful method to reduce the dimensionality of feature vectors for text classification. In this paper, we propose a fuzzy similarity-based self-constructing algorithm for feature clustering. The words in the feature vector of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3e8cdad9503ae9278850f5f35e267b2a
https://doi.org/10.1109/tkde.2010.122
https://doi.org/10.1109/tkde.2010.122
Publikováno v:
Data & Knowledge Engineering. 65:442-462
We develop techniques for discovering patterns with periodicity in this work. Patterns with periodicity are those that occur at regular time intervals, and therefore there are two aspects to the problem: finding the pattern, and determining the perio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bad0266683b2369038a5c6536601e294
https://doi.org/10.1016/j.datak.2007.11.002
https://doi.org/10.1016/j.datak.2007.11.002