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Personalized topic modeling for recommending user-generated content Article

Wei ZHANG, Jia-yu ZHUANG, Xi YONG, Jian-kou LI, Wei CHEN, Zhe-min LI

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 5,   Pages 708-718 doi: 10.1631/FITEE.1500402

Abstract: A generative model that combines hierarchical topic modeling and matrix factorization is proposed.results show that our model outperforms other state-of-the-art models, and can provide interpretable topic

Keywords： User-generated content (UGC)     Collaborative filtering (CF)     Matrix factorization (MF)     Hierarchical topicmodeling    

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Hierarchical modeling of stochastic manufacturing and service systems

Zhe George ZHANG, Xiaoling YIN

Frontiers of Engineering Management 2017, Volume 4, Issue 3,   Pages 295-303 doi: 10.15302/J-FEM-2017047

Abstract: Such a classification unifies stochastic modeling theory.Such models are appropriate for modeling the detailed operations of a manufacturing system with relativelyThese high-level models are appropriate for modeling large-scale service systems with many servers, suchThis review will help practitioners select the appropriate level of modeling to enhance their understanding

Keywords： stochastic modeling     QBD process     PH distribution     heavy traffic limits     diffusion process    

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Emerging topic identification from app reviews via adaptive online biterm topic modeling Research Article

Wan ZHOU, Yong WANG, Cuiyun GAO, Fei YANG,yongwang@ahpu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 5,   Pages 678-691 doi: 10.1631/FITEE.2100465

Abstract: Emerging topics in highlight the topics (e.g., software bugs) with which users are concerned during certain periods. Identifying emerging topics accurately, and in a timely manner, could help developers more effectively update apps. Methods for identifying emerging topics in based on s or clustering methods have been proposed in the literature. However, the accuracy of is reduced because reviews are short in length and offer limited information. To solve this problem, an improved (IETI) approach is proposed in this work. Specifically, we adopt techniques to reduce noisy data, and identify emerging topics in using the adaptive online biterm . Then we interpret the implicature of emerging topics through relevant phrases and sentences. We adopt the official app changelogs as ground truth, and evaluate IETI in six common apps. The experimental results indicate that IETI is more accurate than the baseline in identifying emerging topics, with improvements in the F1 score of 0.126 for phrase labels and 0.061 for sentence labels. Finally, we release the codes of IETI on Github (https://github.com/wanizhou/IETI).

Keywords： App reviews     Emerging topic identification     Topic model     Natural language processing    

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Special Topic on environment and sustainable development

Frontiers of Chemical Science and Engineering 2017, Volume 11, Issue 3,   Pages 291-292 doi: 10.1007/s11705-017-1667-6

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Topicmodeling for large-scale text data

Xi-ming LI,Ji-hong OUYANG

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 6,   Pages 457-465 doi: 10.1631/FITEE.1400352

Abstract: This paper develops a novel online algorithm, namely moving average stochastic variational inference (MASVI), which applies the results obtained by previous iterations to smooth out noisy natural gradients. We analyze the convergence property of the proposed algorithm and conduct a set of experiments on two large-scale collections that contain millions of documents. Experimental results indicate that in contrast to algorithms named ‘stochastic variational inference’ and ‘SGRLD’, our algorithm achieves a faster convergence rate and better performance.

Keywords： Latent Dirichlet allocation (LDA)     Topic modeling     Online learning     Moving average    

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Inverse Gaussian process-based corrosion growth modeling and its application in the reliability analysis

Hao QIN, Shenwei ZHANG, Wenxing ZHOU

Frontiers of Structural and Civil Engineering 2013, Volume 7, Issue 3,   Pages 276-287 doi: 10.1007/s11709-013-0207-9

Abstract: This paper describes an inverse Gaussian process-based model to characterize the growth of metal-loss corrosion defects on energy pipelines. The model parameters are evaluated using the Bayesian methodology by combining the inspection data obtained from multiple inspections with the prior distributions. The Markov Chain Monte Carlo (MCMC) simulation techniques are employed to numerically evaluate the posterior marginal distribution of each individual parameter. The measurement errors associated with the ILI tools are considered in the Bayesian inference. The application of the growth model is illustrated using an example involving real inspection data collected from an in-service pipeline in Alberta, Canada. The results indicate that the model in general can predict the growth of corrosion defects reasonably well. Parametric analyses associated with the growth model as well as reliability assessment of the pipeline based on the growth model are also included in the example. The proposed model can be used to facilitate the development and application of reliability-based pipeline corrosion management.

Keywords： pipeline     metal-loss corrosion     inverse Gaussian process     measurement error     hierarchical Bayesian     Markov    

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Topic discovery and evolution in scientific literature based on content and citations Article

Hou-kui ZHOU, Hui-min YU, Roland HU

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 10,   Pages 1511-1524 doi: 10.1631/FITEE.1601125

Abstract: In this paper, we propose a citation- content-latent Dirichlet allocation (LDA) topic discovery methodThe citation-content-LDA topic model exploits a two-level topic model that includes the citation informationWe also propose a topic evolution algorithm that runs in two steps: topic segmentation and topic dependencyWe have tested the proposed citation-content-LDA model and topic evolution algorithm on two online datasetsSociety (CS), to demonstrate that our algorithm effectively discovers important topics and reflects the topic

Keywords： Topic extraction     Topic evolution     Evaluation method    

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Deep convolutional tree-inspired network: a decision-tree-structured neural network for hierarchical

Frontiers of Mechanical Engineering 2021, Volume 16, Issue 4,   Pages 814-828 doi: 10.1007/s11465-021-0650-6

Abstract: decision-tree-structured neural network, that is, the deep convolutional tree-inspired network (DCTN), for the hierarchicalnetwork (CNN) and decision tree methods by rebuilding the output decision layer of CNN according to the hierarchicalThe proposed DCTN model has unique advantages in 1) the hierarchical structure that can support moreaccuracy and comprehensive fault diagnosis, 2) the better interpretability of the model output with hierarchical

Keywords： bearing     cross-severity fault diagnosis     hierarchical fault diagnosis     convolutional neural network    

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Combined reticular blind drainage and vertical hierarchical drainage system for landfills located in

Wenjing LU,Zhonge FU,Yan ZHAO

Frontiers of Environmental Science & Engineering 2016, Volume 10, Issue 1,   Pages 177-184 doi: 10.1007/s11783-014-0710-9

Abstract: water control technology that combines the features of a reticular blind drainage system and a vertical hierarchicalThe vertical hierarchical drainage system was installed to separate rainfall water and leachate in theleachate derived from rainfall water and groundwater inflow was avoided upon installation of the vertical hierarchical

Keywords： landfill     reticular blind drain     vertical hierarchical drain     guidance and drainage     impermeable layer    

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Effect of hierarchical ZSM-5 zeolite crystal size on diffusion and catalytic performance of n-heptane

Shuman Xu, Xiaoxiao Zhang, Dangguo Cheng, Fengqiu Chen, Xiaohong Ren

Frontiers of Chemical Science and Engineering 2018, Volume 12, Issue 4,   Pages 780-789 doi: 10.1007/s11705-018-1733-8

Abstract: Hierarchical ZSM-5 zeolite aggregates with different sizes of nanocrystals were synthesized using differentCracking over hierarchical zeolites with nanocrystal sizes larger than about 50 nm took place under transition-limitingconditions, whereas the reaction over hierarchical zeolites with nanocrystal sizes of 15 or 30 nm proceededHierarchical ZSM-5 zeolite aggregates with smaller nanocrystals had better selectivity for light olefins

Keywords： hierarchical ZSM-5     crystal size     catalytic cracking     Thiele modulus     effectiveness factor    

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Image meshing via hierarchical optimization

Hao XIE,Ruo-feng TONG

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 1,   Pages 32-40 doi: 10.1631/FITEE.1500171

Abstract: To ameliorate this situation, we present a hierarchical optimization algorithm solving the problem from

Keywords： Image meshing     Hierarchical optimization     Convexification    

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Facile synthesis of hierarchical flower-like Ag/Cu

Mengyun Wang, Shengbo Zhang, Mei Li, Aiguo Han, Xinli Zhu, Qingfeng Ge, Jinyu Han, Hua Wang

Frontiers of Chemical Science and Engineering 2020, Volume 14, Issue 5,   Pages 813-823 doi: 10.1007/s11705-019-1854-8

Abstract: Novel, hierarchical, flower-like Ag/Cu O and Au/Cu O nanostructures were successfully fabricated andBy varying the Ag/Cu atomic ratio, Ag /Cu O, having a hierarchical, flower-like nanostructure with intersectingevolution rate was achieved with Ag /Cu O due to the larger electroactive surface area furnished by the hierarchicalThe same hierarchical flower-like structure was also obtained for the Au /Cu O composite, where the FEThis study presents a facile method of developing hierarchical metal-oxide composites as efficient and

Keywords： bimetallic nanostructure     hierarchical metal/oxide nanomaterial     galvanic replacement     electrochemical reduction    

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Hierarchical parameter estimation of DFIG and drive train system in a wind turbine generator

Xueping PAN, Ping JU, Feng WU, Yuqing JIN

Frontiers of Mechanical Engineering 2017, Volume 12, Issue 3,   Pages 367-376 doi: 10.1007/s11465-017-0429-y

Abstract:

A new hierarchical parameter estimation method for doubly fed induction generator (DFIG) and drive

Keywords： wind turbine generator     DFIG     drive train system     hierarchical parameter estimation method     trajectory sensitivity    

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The Immense Impact of Reverse Edges on Large Hierarchical Networks

Haosen Cao,Bin-Bin Hu,Xiaoyu Mo,Duxin Chen,Jianxi Gao,Ye Yuan,Guanrong Chen,Tamás Vicsek,Xiaohong Guan,Hai-Tao Zhang,

Engineering doi: 10.1016/j.eng.2023.06.011

Abstract: Hierarchical networks are frequently encountered in animal groups, gene networks, and artificial engineeringThe structure of a large directed hierarchical network is often strongly influenced by reverse edgesThis study reveals that, for most large-scale real hierarchical networks, the majority of the reverseMore surprisingly, a single effective reverse edge can slow down the synchronization of a huge hierarchicalOur study also proposes an effective way to attack a hierarchical network by adding a malicious reverse

Keywords： Synchronizability     Large hierarchical networks     Reverse edges     Information flows     Complex networks    

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Erratum to: Synthesis of hierarchical nanohybrid CNT@Ni-PS and its applications in enhancing the tribological

Frontiers of Chemical Science and Engineering 2022, Volume 16, Issue 10,   Pages 1530-1530 doi: 10.1007/s11705-022-2240-5

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Title Author Date Type Operation

Personalized topic modeling for recommending user-generated content

Wei ZHANG, Jia-yu ZHUANG, Xi YONG, Jian-kou LI, Wei CHEN, Zhe-min LI

Journal Article

Hierarchical modeling of stochastic manufacturing and service systems

Zhe George ZHANG, Xiaoling YIN

Journal Article

Emerging topic identification from app reviews via adaptive online biterm topic modeling

Wan ZHOU, Yong WANG, Cuiyun GAO, Fei YANG,yongwang@ahpu.edu.cn

Journal Article

Special Topic on environment and sustainable development

Journal Article

Topicmodeling for large-scale text data

Xi-ming LI,Ji-hong OUYANG

Journal Article

Inverse Gaussian process-based corrosion growth modeling and its application in the reliability analysis

Hao QIN, Shenwei ZHANG, Wenxing ZHOU

Journal Article

Topic discovery and evolution in scientific literature based on content and citations

Hou-kui ZHOU, Hui-min YU, Roland HU

Journal Article

Deep convolutional tree-inspired network: a decision-tree-structured neural network for hierarchical

Journal Article

Combined reticular blind drainage and vertical hierarchical drainage system for landfills located in

Wenjing LU,Zhonge FU,Yan ZHAO

Journal Article

Effect of hierarchical ZSM-5 zeolite crystal size on diffusion and catalytic performance of n-heptane

Shuman Xu, Xiaoxiao Zhang, Dangguo Cheng, Fengqiu Chen, Xiaohong Ren

Journal Article

Image meshing via hierarchical optimization

Hao XIE,Ruo-feng TONG

Journal Article

Facile synthesis of hierarchical flower-like Ag/Cu

Mengyun Wang, Shengbo Zhang, Mei Li, Aiguo Han, Xinli Zhu, Qingfeng Ge, Jinyu Han, Hua Wang

Journal Article

Hierarchical parameter estimation of DFIG and drive train system in a wind turbine generator

Xueping PAN, Ping JU, Feng WU, Yuqing JIN

Journal Article

The Immense Impact of Reverse Edges on Large Hierarchical Networks

Haosen Cao,Bin-Bin Hu,Xiaoyu Mo,Duxin Chen,Jianxi Gao,Ye Yuan,Guanrong Chen,Tamás Vicsek,Xiaohong Guan,Hai-Tao Zhang,

Journal Article

Erratum to: Synthesis of hierarchical nanohybrid CNT@Ni-PS and its applications in enhancing the tribological

Journal Article