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Self-supervised graph learning with target-adaptive masking for session-based recommendation Research Article

Yitong WANG, Fei CAI, Zhiqiang PAN, Chengyu SONG,wangyitong20@nudt.edu.cn,caifei08@nudt.edu.cn,panzhiqiang@nudt.edu.cn,songchengyu@nudt.edu.cn

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 1,   Pages 73-87 doi: 10.1631/FITEE.2200137

Abstract: aims to predict the next item based on a user's limited interactions within a short period.Specifically, we first construct a global graph based on all involved sessions and subsequently captureitems, which helps supervise the model in generating accurate representations of items in the ongoing session

Keywords： Session-based recommendation     Self-supervised learning     Graph neural networks     Target-adaptive masking    

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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 interestIn addition, to address the user cold-start problem, a social tag prediction algorithm based on communityA 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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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 theThis non-IID recommendation research triggers the paradigm shift from IID to non-IID recommendation researchdirections and fundamental solutions to address various complexities including cold-start, sparse data-based, cross-domain, group-based, and shilling attack-related issues.

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

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RepoLike: amulti-feature-based personalized recommendation approach for open-source repositories None

Cheng YANG, Qiang FAN, Tao WANG, Gang YIN, Xun-hui ZHANG, Yue YU, Hua-min WANG

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 2,   Pages 222-237 doi: 10.1631/FITEE.1700196

Abstract: In this paper, we propose a new approach called “RepoLike,” to recommend repositories for developers based

Keywords： Social coding     Open-source software     Personal recommendation     GitHub    

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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 forWe present the general architecture of personalized recommendation systems, the privacy issues therein, 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: Their low incidence and drastic regional disparities result in the difficulty of informative evidence-basedLastly, 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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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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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 sociallinearly discretize the user’s spatiotemporal information and then use recurrent neural network (RNN) based

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: have led to the low accuracy in traditional algorithms, thus leading to the emergence of systems basedin this paper we propose a feedforward deep method, called the deep association (DAN), which is based

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

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Fast code recommendation via approximate sub-tree matching Research Article

Yichao SHAO, Zhiqiu HUANG, Weiwei LI, Yaoshen YU,shaoyichao@nuaa.edu.cn,zqhuang@nuaa.edu.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 8,   Pages 1205-1216 doi: 10.1631/FITEE.2100379

Abstract: We propose an approximate sub-tree matching based method to solve this problem.Unlike existing tree-based approaches that match feature vectors, it retains the tree structure of the

Keywords： Code reuse     Code recommendation     Tree similarity     Structure information    

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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: We present an effective taxi approach (called APFD) based on the (APF) method and method with mobileThen, based on the APF method, we put forward an effective approach for removing redundant nodes.

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

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A knowledge-guided and traditional Chinese medicine informed approach for herb recommendation Research Article

Zhe JIN, Yin ZHANG, Jiaxu MIAO, Yi YANG, Yueting ZHUANG, Yunhe PAN,11521043@zju.edu.cn,yinzh@zju.edu.cn

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 10,   Pages 1416-1429 doi: 10.1631/FITEE.2200662

Abstract: This involves appropriately recommending a set of herbs based on patients’ symptoms.

Keywords： Traditional Chinese medicine     Herb recommendation     Knowledge graph     Graph attention network    

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Phosphorus supply and management in vegetable production systems in China

Rui WANG, Weiming SHI, Yilin LI

Frontiers of Agricultural Science and Engineering 2019, Volume 6, Issue 4,   Pages 348-356 doi: 10.15302/J-FASE-2019277

Abstract:

Vegetable production systems involve high rates of chemical and organic fertilizer applications, leading to significant P accumulation in vegetable soils, as well as a decrease in P use efficiency (PUE), which is one of the key limiting factors in vegetable production. This review introduces the vegetable production systems in China and their fertilization status, and analyzes probable causes of overfertilization of vegetable fields. Poorly developed root systems and high P demand have led to the need to maintain much higher available P concentrations in the root zone for regular growth of vegetables, which might necessitate higher phosphate fertilizer input than the plants require. Research on strategies to improve vegetable PUE and the mechanisms of these strategies are summarized in this review. Increasing the P uptake by vegetables by supplying P during the critical growth stage and effectively utilizing the accumulated P by optimizing the C:P ratio in soils can substantially increase PUE. These advances will provide a basis for improving PUE and optimizing phosphate fertilizer applications in vegetable production through regulatory measures. In addition, some policies are recommended that could ensure the safety of vegetables and improve product quality. This review also aims to improve understanding of P cycling in vegetable fields and assist in the development of best practices to manage P reserves globally.

Keywords： phosphate fertilizer     phosphorus use efficiency     vegetable production systems     phosphorus management     policy recommendation    

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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: To tackle these challenges, we propose a novel explainable recommendation approach for extended kindsA 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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Finding map regions with high density of query keywords Article

Zhi YU, Can WANG, Jia-jun BU, Xia HU, Zhe WANG, Jia-he JIN

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 10,   Pages 1543-1555 doi: 10.1631/FITEE.1600043

Abstract: This region search problem can be applied in many practical scenarios such as shopping recommendation

Keywords： Map search     Region search     Region recommendation     Spatial keyword search     Geographic information system     Location-based service    

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Title Author Date Type Operation

Self-supervised graph learning with target-adaptive masking for session-based recommendation

Yitong WANG, Fei CAI, Zhiqiang PAN, Chengyu SONG,wangyitong20@nudt.edu.cn,caifei08@nudt.edu.cn,panzhiqiang@nudt.edu.cn,songchengyu@nudt.edu.cn

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

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

Longbing Cao

Journal Article

RepoLike: amulti-feature-based personalized recommendation approach for open-source repositories

Cheng YANG, Qiang FAN, Tao WANG, Gang YIN, Xun-hui ZHANG, Yue YU, Hua-min WANG

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

EncyCatalogRec: catalog recommendation for encyclopedia article completion

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

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

Fast code recommendation via approximate sub-tree matching

Yichao SHAO, Zhiqiu HUANG, Weiwei LI, Yaoshen YU,shaoyichao@nuaa.edu.cn,zqhuang@nuaa.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

A knowledge-guided and traditional Chinese medicine informed approach for herb recommendation

Zhe JIN, Yin ZHANG, Jiaxu MIAO, Yi YANG, Yueting ZHUANG, Yunhe PAN,11521043@zju.edu.cn,yinzh@zju.edu.cn

Journal Article

Phosphorus supply and management in vegetable production systems in China

Rui WANG, Weiming SHI, Yilin LI

Journal Article

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

Finding map regions with high density of query keywords

Zhi YU, Can WANG, Jia-jun BU, Xia HU, Zhe WANG, Jia-he JIN

Journal Article