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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: Software developers often write code that has similar functionality to existing code segments.A tool that helps developers reuse these code fragments can significantly improve their efficiency.Most of these methods are time-consuming and can leverage only low-level textual information from codeOthers extract features from code and obtain similarity using numerical feature vectors.in the matching process to find code fragments that best match the current query.

Keywords： Code reuse     Code recommendation     Tree similarity     Structure information    

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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 research

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

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Optimization of spatial structure designs of control rod using Monte Carlo code RMC

Frontiers in Energy 2021, Volume 15, Issue 4,   Pages 974-983 doi: 10.1007/s11708-021-0769-5

Abstract: rod worth and effective absorption cross section of these designs are computed using the Monte Carlo code

Keywords： control rod     optimized spatial structure     neutronic performance     burnup stability    

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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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EAI-oriented information classification code system in manufacturing enterprises

WANG Junbiao, DENG Hu, JIANG Jianjun, YANG Binghong, WANG Bailing

Frontiers of Mechanical Engineering 2008, Volume 3, Issue 1,   Pages 81-85 doi: 10.1007/s11465-008-0011-8

Abstract: information classification coding system in manufacturing enterprises (MEs) emphasizes the construction of codestandards, it lacks the management of the code creation, code data transmission and so on.manufacturing enterprises, an enterprise application integration oriented information classification codeEAIO-ICCS expands the connotation of the information classification code system and assures the identity

Keywords： EAI     EAIO-ICCS     management     classification     connotation    

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A MATLAB code for the material-field series-expansion topology optimization method

Frontiers of Mechanical Engineering 2021, Volume 16, Issue 3,   Pages 607-622 doi: 10.1007/s11465-021-0637-3

Abstract: With the focus on the implementation of the MFSE method, the present MATLAB code uses the maximum stiffnessThe MATLAB code consists of three parts, namely, the main program and two subroutines (one for aggregatingThe implementation of the code and its extensions to topology optimization problems with multiple loadThe code is intended for researchers who are interested in this method and want to get started with it

Keywords： MATLAB implementation     topology optimization     material-field series-expansion method     bounded material field     dimensionality reduction    

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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: Lastly, 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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An incremental software architecture recovery technique driven by code changes Research Article

Li WANG, Xianglong KONG, Jiahui WANG, Bixin LI,wangli1218@seu.edu.cn,xlkong@seu.edu.cn,18262609320@163.com,bx.li@seu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 5,   Pages 664-677 doi: 10.1631/FITEE.2100461

Abstract: Our technique obtains dependency information from changed code blocks and identifies different strength-levelThen, we use double classifiers to recover the architecture based on the method of mapping code-level

Keywords： Architecture recovery     Software evolution     Code change    

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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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ShortTail: taming tail latency for erasure-code-based in-memory systems Research Article

Yun TENG, Zhiyue LI, Jing HUANG, Guangyan ZHANG

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 11,   Pages 1646-1657 doi: 10.1631/FITEE.2100566

Abstract:

s with erasure coding (EC) enabled are widely used to achieve high performance and data availability. However, as the scale of clusters grows, the server-level fail-slow problem is becoming increasingly frequent, which can create long . The influence of long is further amplified in EC-based systems due to the synchronous nature of multiple EC sub-operations. In this paper, we propose an EC-enabled in-memory storage system called ShortTail, which can achieve consistent performance and low latency for both reads and writes. First, ShortTail uses a lightweight request monitor to track the performance of each memory node and identify any fail-slow node. Second, ShortTail selectively performs degraded reads and redirected writes to avoid accessing fail-slow nodes. Finally, ShortTail posts an adaptive write strategy to reduce write amplification of s. We implement ShortTail on top of Memcached and compare it with two baseline systems. The experimental results show that ShortTail can reduce the P99 by up to 63.77%; it also brings significant improvements in the median latency and average latency.

Keywords： Erasure code     In-memory system     Node fail-slow     Small write     Tail latency    

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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 social

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. The traditional matrix decomposition algorithm simply decomposes users and items into a linear model of potential factors. These limitations have led to the low accuracy in traditional algorithms, thus leading to the emergence of systems based on . At present, s mostly use deep s to model some of the auxiliary information, and in the process of modeling, multiple mapping paths are adopted to map the original input data to the potential vector space. However, these deep algorithms ignore the combined effects of different categories of data, which can have a potential impact on the effectiveness of the . Aimed at this problem, in this paper we propose a feedforward deep method, called the deep association (DAN), which is based on the joint action of multiple categories of information, for implicit feedback . Specifically, the underlying input of the model includes not only users and items, but also more auxiliary information. In addition, the impact of the joint action of different types of information on the is considered. Experiments on an open data set show the significant improvements made by our proposed method over the other methods. Empirical evidence shows that deep, joint s can provide better performance.

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

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Development of a steady thermal-hydraulic analysis code for the China Advanced Research Reactor

TIAN Wenxi, QIU Suizheng, GUO Yun, SU Guanghui, JIA Dounan, LIU Tiancai, ZHANG Jianwei

Frontiers in Energy 2007, Volume 1, Issue 2,   Pages 189-194 doi: 10.1007/s00000-007-0024-8

Abstract: A multi-channel model steady-state thermal-hydraulic analysis code was developed for the China Advanced

Keywords： detailed     calculation     unsymmetrical     temperature     channel    

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The Rise of No/Low Code Software Development—No Experience Needed?

Marcus Woo

Engineering 2020, Volume 6, Issue 9,   Pages 960-961 doi: 10.1016/j.eng.2020.07.007

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Title Author Date Type Operation

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

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

Longbing Cao

Journal Article

Optimization of spatial structure designs of control rod using Monte Carlo code RMC

Journal Article

Toward Privacy-Preserving Personalized Recommendation Services

Cong Wang, Yifeng Zheng, Jinghua Jiang, Kui Ren

Journal Article

EAI-oriented information classification code system in manufacturing enterprises

WANG Junbiao, DENG Hu, JIANG Jianjun, YANG Binghong, WANG Bailing

Journal Article

A MATLAB code for the material-field series-expansion topology optimization method

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

An incremental software architecture recovery technique driven by code changes

Li WANG, Xianglong KONG, Jiahui WANG, Bixin LI,wangli1218@seu.edu.cn,xlkong@seu.edu.cn,18262609320@163.com,bx.li@seu.edu.cn

Journal Article

EncyCatalogRec: catalog recommendation for encyclopedia article completion

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

Journal Article

ShortTail: taming tail latency for erasure-code-based in-memory systems

Yun TENG, Zhiyue LI, Jing HUANG, Guangyan ZHANG

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

Development of a steady thermal-hydraulic analysis code for the China Advanced Research Reactor

TIAN Wenxi, QIU Suizheng, GUO Yun, SU Guanghui, JIA Dounan, LIU Tiancai, ZHANG Jianwei

Journal Article

The Rise of No/Low Code Software Development—No Experience Needed?

Marcus Woo

Journal Article