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Explainable data transformation recommendation for automatic visualization Research Article

Ziliang WU, Wei CHEN, Yuxin MA, Tong XU, Fan YAN, Lei LV, Zhonghao QIAN, Jiazhi XIA,wzlzju@zju.edu.cn,chenvis@zju.edu.cn

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 7,   Pages 1007-1027 doi: 10.1631/FITEE.2200409

Abstract: generates meaningful visualizations to support data analysis and pattern finding for novice or casualCurrent approaches adopt mainly aggregation and filtering to extract patterns from the original dataTo tackle these challenges, we propose a novel explainable recommendation approach for extended kindsWe summarize the space of feasible s and measures on of transformation operations with a literatureA recommendation algorithm is designed to compute optimal transformations, which can reveal specified

Keywords： Data transformation     Data transformation recommendation     Automatic visualization     Explainability    

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APFD: an effective approach to taxi route recommendation with mobile trajectory big data Research Article

Wenyong ZHANG, Dawen XIA, Guoyan CHANG, Yang HU, Yujia HUO, Fujian FENG, Yantao LI, Huaqing LI

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 10,   Pages 1494-1510 doi: 10.1631/FITEE.2100530

Abstract:

With the rapid development of data-driven intelligent transportation systems, an efficient methodeffective taxi approach (called APFD) based on the (APF) method and method with mobile trajectory big data

Keywords： Big data analytics     Region extraction     Artificial potential field     Dijkstra     Route recommendation     GPS    

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Study on Data Locality and Its Optimization Technologies in Multiprocessor Systems

Yang Xuejun,Dai Huadong,Xia Jun

Strategic Study of CAE 2002, Volume 4, Issue 5,   Pages 44-52

Abstract:

As one of the most important issues in multiprocessor systems, data locality is a main direction ofachievements by the authors with the current state of studies in this field, a systematic discussion on dataBesides, from the viewpoint of static locality optimization technologies, a data transformation framework

Keywords： computer     multiprocessorsystem     data locality     locality measurement model     data transformation framework    

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Lifecycle Data Management of Nuclear Power Plant: Framework System and Development Suggestions

Ren Jingli, Yang Pan

Strategic Study of CAE 2022, Volume 24, Issue 2,   Pages 152-159 doi: 10.15302/J-SSCAE-2022.02.012

Abstract:

As the digital and intelligent transformation of the nuclear industrystandards; (2) classifying the lifecycle data according to data types and reasonably designing the datamodels; and (3) scientifically formulating data quality control policies and data quality measurement, business data, and three-dimensional simulation data in the nuclear power plants to promote the interconnectionlifecycle data management to ensure the authenticity and traceability of the data; (3) digital twins

Keywords： digital transformation     nuclear power plant     lifecycle     data management     framework system    

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Non-IID Recommender Systems: A Review and Framework of Recommendation Paradigm Shifting Artical

Longbing Cao

Engineering 2016, Volume 2, Issue 2,   Pages 212-224 doi: 10.1016/J.ENG.2016.02.013

Abstract:

While recommendation plays an increasingly critical role in our living, study, work, and entertainmentIn this paper, the non-IID nature and characteristics of recommendation are discussed, followed by thetheoretical framework in order to build a deep and comprehensive understanding of the intrinsic nature of recommendationThis non-IID recommendation research triggers the paradigm shift from IID to non-IID recommendation researchnew directions and fundamental solutions to address various complexities including cold-start, sparse data-based

Keywords： relationship     Coupling learning     Relational learning     IIDness learning     Non-IIDness learning     Recommender system     Recommendation     Non-IID recommendation    

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Toward Privacy-Preserving Personalized Recommendation Services Review

Cong Wang, Yifeng Zheng, Jinghua Jiang, Kui Ren

Engineering 2018, Volume 4, Issue 1,   Pages 21-28 doi: 10.1016/j.eng.2018.02.005

Abstract:

Recommendation systems are crucially important for the delivery of personalized services to users.With personalized recommendation services, users can enjoy a variety of targeted recommendations suchIn addition, personalized recommendation services have become extremely effective revenue drivers forof users’ personal data for processing and analytics, which undesirably makes users susceptible, and existing works that focus on privacy-preserving personalized recommendation services.

Keywords： Privacy protection     Personalized recommendation services     Targeted delivery     Collaborative filtering     Machine    

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Rare tumors: a blue ocean of investigation

Frontiers of Medicine 2023, Volume 17, Issue 2,   Pages 220-230 doi: 10.1007/s11684-023-0984-z

Abstract: Herein, by reviewing the epidemiological data of Chinese solid tumors and publications defining rareLastly, we pinpointed the current recommendation chance for patients with rare tumors to be involved

Keywords： rare tumors     diagnosis flowchart     treatment strategy     clinical trials recommendation    

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A microblog recommendation algorithm based on social tagging and a temporal interest evolution model

Zhen-ming YUAN,Chi HUANG,Xiao-yan SUN,Xing-xing LI,Dong-rong XU

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 7,   Pages 532-540 doi: 10.1631/FITEE.1400368

Abstract: In this paper, we propose a collaborative filtering recommendation algorithm based on a temporal interestA questionnaire survey proved user satisfaction with recommendation results when the cold-start problem

Keywords： Recommender system     Collaborative filtering     Social tagging     Interest evolution model    

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EncyCatalogRec: catalog recommendation for encyclopedia article completion Article

Wei-ming LU, Jia-hui LIU, Wei XU, Peng WANG, Bao-gang WEI

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 3,   Pages 436-447 doi: 10.1631/FITEE.1800363

Abstract: So, the recommendation problem is changed to a transductive learning problem in the product graph.Experimental results demonstrate that our approach achieves state-of-the-art performance on catalog recommendation

Keywords： Catalog recommendation     Encyclopedia article completion     Product graph     Transductive learning    

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Transformation of triclosan by a novel cold-adapted laccase from

Yuanyuan Shi, Deyang Kong, Jiayang Liu, Junhe Lu, Xiaoming Yin, Quansuo Zhou

Frontiers of Environmental Science & Engineering 2017, Volume 11, Issue 3, doi: 10.1007/s11783-017-0927-5

Abstract: This work investigated the transformation of triclosan (TCS) by laccase produced by a pathogen isolatedTransformation products of TCS were analyzed by mass spectrometry and it was revealed that TCS dimerswidely presented in natural environment, this study also revealed an important pathway involved in the transformation

Keywords： Laccase     Botrytis cinerea     Triclosan     Transformation     Kinetics    

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Exploring nonlinear spatiotemporal effects for personalized next point-of-interest recommendation

孙曦,吕志民

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 9,   Pages 1273-1286 doi: 10.1631/FITEE.2200304

Abstract: Next point-of-interest (POI) recommendation is an important personalized task in location-based socialLBSNs) and aims to recommend the next POI for users in a specific situation with historical check-in data

Keywords： Point-of-interest recommendation     Spatiotemporal effects     Long short-term memory (LSTM)     Attention mechanism    

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DAN: a deep association neural network approach for personalization recommendation Research Articles

Xu-na Wang, Qing-mei Tan,Xuna@nuaa.edu.cn,tanchina@nuaa.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 7,   Pages 963-980 doi: 10.1631/FITEE.1900236

Abstract: The collaborative filtering technology used in traditional systems has a problem of data sparsity.information, and in the process of modeling, multiple mapping paths are adopted to map the original input dataHowever, these deep algorithms ignore the combined effects of different categories of data, which canExperiments on an open data set show the significant improvements made by our proposed method over the

Keywords： Neural network     Deep learning     Deep association neural network (DAN)     Recommendation    

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Outliers detection algorithm based on nonlinear data transformation

Xu Xuesong,Zhang Xu,Song Dongming,Zhang Hong,Liu Fnegyu

Strategic Study of CAE 2008, Volume 10, Issue 9,   Pages 74-78

Abstract:

The data dimension reduction is the main method that can enhance theoutliers mining efficiency based on higher-dimension data set.into linear data in the feature space,and introduce a nonlinear data transformation to reduce data dimensionOn the basis of each resulting vector,it determins whether the data is outlier data or not one by oneused to detect nonlinear inseparable outlier data.

Keywords： dimension reduction     kernel function     principal component     outliers    

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FOOD SYSTEMS TRANSFORMATION: CONCEPTS, MECHANISMS AND PRACTICES

Frontiers of Agricultural Science and Engineering 2023, Volume 10, Issue 1,   Pages 1-3 doi: 10.15302/J-FASE-2023491

Abstract: FOOD SYSTEMS TRANSFORMATION: CONCEPTS, MECHANISMS AND PRACTICES

Keywords： TRANSFORMATION     SYSTEMS     FOOD     CONCEPTS     MECHANISMS    

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TRANSFORMATION OF FOOD SYSTEMS: HOW CAN IT BE FINANCED?

Frontiers of Agricultural Science and Engineering 2023, Volume 10, Issue 1,   Pages 109-123 doi: 10.15302/J-FASE-2023483

Abstract:

● The analysis of financing for the transformation of food systems

Keywords： financial markets     food systems     development financing     consumer expenditures     public budgets     Sustainable Development Goals    

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Title Author Date Type Operation

Explainable data transformation recommendation for automatic visualization

Ziliang WU, Wei CHEN, Yuxin MA, Tong XU, Fan YAN, Lei LV, Zhonghao QIAN, Jiazhi XIA,wzlzju@zju.edu.cn,chenvis@zju.edu.cn

Journal Article

APFD: an effective approach to taxi route recommendation with mobile trajectory big data

Wenyong ZHANG, Dawen XIA, Guoyan CHANG, Yang HU, Yujia HUO, Fujian FENG, Yantao LI, Huaqing LI

Journal Article

Study on Data Locality and Its Optimization Technologies in Multiprocessor Systems

Yang Xuejun,Dai Huadong,Xia Jun

Journal Article

Lifecycle Data Management of Nuclear Power Plant: Framework System and Development Suggestions

Ren Jingli, Yang Pan

Journal Article

Non-IID Recommender Systems: A Review and Framework of Recommendation Paradigm Shifting

Longbing Cao

Journal Article

Toward Privacy-Preserving Personalized Recommendation Services

Cong Wang, Yifeng Zheng, Jinghua Jiang, Kui Ren

Journal Article

Rare tumors: a blue ocean of investigation

Journal Article

A microblog recommendation algorithm based on social tagging and a temporal interest evolution model

Zhen-ming YUAN,Chi HUANG,Xiao-yan SUN,Xing-xing LI,Dong-rong XU

Journal Article

EncyCatalogRec: catalog recommendation for encyclopedia article completion

Wei-ming LU, Jia-hui LIU, Wei XU, Peng WANG, Bao-gang WEI

Journal Article

Transformation of triclosan by a novel cold-adapted laccase from

Yuanyuan Shi, Deyang Kong, Jiayang Liu, Junhe Lu, Xiaoming Yin, Quansuo Zhou

Journal Article

Exploring nonlinear spatiotemporal effects for personalized next point-of-interest recommendation

孙曦,吕志民

Journal Article

DAN: a deep association neural network approach for personalization recommendation

Xu-na Wang, Qing-mei Tan,Xuna@nuaa.edu.cn,tanchina@nuaa.edu.cn

Journal Article

Outliers detection algorithm based on nonlinear data transformation

Xu Xuesong,Zhang Xu,Song Dongming,Zhang Hong,Liu Fnegyu

Journal Article

FOOD SYSTEMS TRANSFORMATION: CONCEPTS, MECHANISMS AND PRACTICES

Journal Article

TRANSFORMATION OF FOOD SYSTEMS: HOW CAN IT BE FINANCED?

Journal Article