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Institution

Chung Yuan Christian University

EducationTaoyuan City, Taiwan
About: Chung Yuan Christian University is a education organization based out in Taoyuan City, Taiwan. It is known for research contribution in the topics: Membrane & Fuzzy logic. The organization has 9819 authors who have published 11623 publications receiving 213139 citations. The organization is also known as: Tiong-gôan-tāi-ha̍k & CYCU.


Papers
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Journal ArticleDOI
01 Apr 2012
TL;DR: The experimental results based on the Movielens dataset show that cluster ensembles can provide better recommendation performance than single clustering techniques in terms of recommendation accuracy and precision.
Abstract: Recommender systems, which recommend items of information that are likely to be of interest to the users, and filter out less favored data items, have been developed. Collaborative filtering is a widely used recommendation technique. It is based on the assumption that people who share the same preferences on some items tend to share the same preferences on other items. Clustering techniques are commonly used for collaborative filtering recommendation. While cluster ensembles have been shown to outperform many single clustering techniques in the literature, the performance of cluster ensembles for recommendation has not been fully examined. Thus, the aim of this paper is to assess the applicability of cluster ensembles to collaborative filtering recommendation. In particular, two well-known clustering techniques (self-organizing maps (SOM) and k-means), and three ensemble methods (the cluster-based similarity partitioning algorithm (CSPA), hypergraph partitioning algorithm (HGPA), and majority voting) are used. The experimental results based on the Movielens dataset show that cluster ensembles can provide better recommendation performance than single clustering techniques in terms of recommendation accuracy and precision. In addition, there are no statistically significant differences between either the three SOM ensembles or the three k-means ensembles. Either the SOM or k-means ensembles could be considered in the future as the baseline collaborative filtering technique.

122 citations

Journal ArticleDOI
TL;DR: A novel "one-pot" strategy for preparation of chitosan-coated carbon nanotubes (CNTs) composites via a combination of Diels-Alder (DA) reaction and mercaptoacetic acid locking imine (MALI) reaction for the first time is reported.

122 citations

Journal ArticleDOI
TL;DR: In this paper, an integrated model for achieving multiple targets in measuring service quality is presented, i.e. to identify the important quality attributes that are identified by customers; to understand customer satisfaction levels with respect to these quality attributes; to discover the difference between employees' perceptions and the customers' perceptions of these quality attribute; to use the analytic results to improve service quality; and to identify categories of Kano's model of each quality attribute that can be used as critical reference on quality decisions.
Abstract: The improvement of service quality has become a major strategy for improving competitiveness. The identification of customers’ requirements and the measurement of satisfaction levels are therefore two crucial activities for enterprises. However, firms frequently fail to understand customer requirements, and the usual methods for measuring customer satisfaction are incomplete. The present research establishes an integrated model for achieving multiple targets in measuring service quality, i.e. to identify the important quality attributes that are identified by customers; to understand customer satisfaction levels with respect to these quality attributes; to discover the difference between employees’ perceptions and the customers’ perceptions of these quality attributes; to use the analytic results to improve service quality; and to identify the categories of Kano’s model of each quality attribute that can be used as critical reference on quality decisions. This integrated model is valuable for practical implementation in industries, and as an important reference for academic research on service quality.

122 citations

Journal ArticleDOI
TL;DR: A profound variation in the performance of CANON process was experienced at high DO exposure and high nitrite concentration, whereas the synergistic inhibition of nitrite, free ammonia and free nitrous acid was irreversible.

121 citations

Journal ArticleDOI
TL;DR: In this paper, the absorption of CO2 into monoethanolamine (MEA) and triethanolamines (TEA) + water were investigated at 30, 35, and 40 °C using a laboratory wetted wall column.
Abstract: Kinetics of the absorption of CO2 into monoethanolamine (MEA) + triethanolamine (TEA) + water were investigated at 30, 35, and 40 °C using a laboratory wetted wall column. Ten systems of which 0.5 and 1.0 kmol m-3 TEA mixed with various MEA concentrations (0.1, 0.2, 0.3, 0.4, and 0.5 kmol m-3) were studied. Densities and viscosities of 10 blended-amine systems and solubilities and diffusivities of N2O in the solutions were measured. The N2O analogy was applied to estimate the solubilities and diffusivities of CO2 in amine systems. On the basis of the fast pseudo-first-order rate for CO2 absorption, the overall pseudo-first-order reaction rate constants were determined from kinetic measurements. The addition of small amounts of MEA to TEA results in a significant enhancement of CO2 absorption rates. A hybrid reaction rate model, a zwitterion mechanism for MEA and a first-order reaction for TEA, was used to model the kinetic data. The model is satisfactory to represent CO2 absorption rates in TEA + MEA aque...

121 citations


Authors

Showing all 9844 results

NameH-indexPapersCitations
Simon Lin12675469084
Xiaodong Li104130049024
Yu Wang92168747472
Leaf Huang9235025867
Duu-Jong Lee9197937292
Yen Wei8564925805
Ru-Shi Liu8273826699
Kazuhiko Ishihara7771324795
Gwo-Hshiung Tzeng7746526807
Huan-Tsung Chang7640521476
Hari M. Srivastava76112642635
Jianhua Yang7455427839
Yen Wei6830917527
Hsisheng Teng6721314408
Kevin C.-W. Wu6627815193
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202315
202271
2021590
2020633
2019569
2018514