Resource Type

Journal Article 84

Year

2023 10

2022 5

2021 5

2020 11

2019 3

2018 6

2017 10

2016 6

2015 5

2014 1

2012 1

2011 1

2010 4

2009 1

2008 2

2007 6

2006 1

2005 1

2004 2

2002 1

open ︾

Keywords

Collaborative filtering 5

Kalman filtering 3

collaboration 3

collaborative development 3

4D BIM 2

IFC 2

Kalman filter 2

Recommender systems 2

big data 2

blockchain 2

collaborative innovation 2

2R1T spindle head 1

3D packaging devices 1

4D BIM use 1

AEC project management 1

Adaptive beamforming 1

Adaptive quantum genetic algorithm 1

Alternate vertex updating 1

Antenna array 1

open ︾

Search scope:

排序： Display mode:

Preference transfer model in collaborative filtering for implicit data Project supported by Article

Bin JU,Yun-tao QIAN,Min-chao YE

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 6,   Pages 489-500 doi: 10.1631/FITEE.1500313

Abstract: item will be liked or disliked by active users, and how much an item will be liked, is a main task of collaborativefiltering systems or recommender systems.predicting most likely bought items for a target user, which is a subproblem of the rank problem of collaborativefiltering, became an important task in collaborative filtering.filtering.

Keywords： Recommender systems     Collaborative filtering     Preference transfer model     Cross domain     Implicit data    

HTML PDF Collect

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 interest

Keywords： Recommender system     Collaborative filtering     Social tagging     Interest evolution model    

HTML PDF Collect

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 such as movies, books, ads, restaurants, and more. In addition, personalized recommendation services have become extremely effective revenue drivers for online business. Despite the great benefits, deploying personalized recommendation services typically requires the collection of users’ personal data for processing and analytics, which undesirably makes users susceptible to serious privacy violation issues. Therefore, it is of paramount importance to develop practical privacy-preserving techniques to maintain the intelligence of personalized recommendation services while respecting user privacy. In this paper, we provide a comprehensive survey of the literature related to personalized recommendation services with privacy protection. We present the general architecture of personalized recommendation systems, the privacy issues therein, and existing works that focus on privacy-preserving personalized recommendation services. We classify the existing works according to their underlying techniques for personalized recommendation and privacy protection, and thoroughly discuss and compare their merits and demerits, especially in terms of privacy and recommendation accuracy. We also identity some future research directions.

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

HTML PDF Collect

A new item-based deep network structure using a restricted Boltzmann machine for collaborative filtering Article

Yong-ping DU, Chang-qing YAO, Shu-hua HUO, Jing-xuan LIU

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 5,   Pages 658-666 doi: 10.1631/FITEE.1601732

Abstract: The collaborative filtering (CF) technique has been widely used recently in recommendation systems.

Keywords： Restricted Boltzmann machine     Deep network structure     Collaborative filtering     Recommendation system    

HTML PDF Collect

An application of game theory in distributed collaborative decision making

Angran XIAO

Frontiers of Mechanical Engineering 2019, Volume 14, Issue 1,   Pages 85-101 doi: 10.1007/s11465-019-0523-4

Abstract: realization environment, new paradigms and accompanying software systems are necessary to support the collaborativeof principles from game theory to model the relationships between engineering teams and facilitate collaborative

Keywords： collaboration     distributed product realization     game theory     digital interface    

HTML PDF Collect

A novel confidence estimation method for heterogeneous implicit feedback Article

Jing WANG, Lan-fen LIN, Heng ZHANG, Jia-qi TU, Peng-hua YU

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 11,   Pages 1817-1827 doi: 10.1631/FITEE.1601468

Abstract: Implicit feedback, which indirectly reflects opinion through user behaviors, has gained increasing attention in rec-ommender system communities due to its accessibility and richness in real-world applications. A major way of exploiting implicit feedback is to treat the data as an indication of positive and negative preferences associated with vastly varying confidence levels. Such algorithms assume that the numerical value of implicit feedback, such as time of watching, indicates confidence, rather than degree of preference, and a larger value indicates a higher confidence, although this works only when just one type of implicit feedback is available. However, in real-world applications, there are usually various types of implicit feedback, which can be referred to as heterogeneous implicit feedback. Existing methods cannot efficiently infer confidence levels from heterogeneous implicit feedback. In this paper, we propose a novel confidence estimation approach to infer the confidence level of user prefer-ence based on heterogeneous implicit feedback. Then we apply the inferred confidence to both point-wise and pair-wise matrix factorization models, and propose a more generic strategy to select effective training samples for pair-wise methods. Experiments on real-world e-commerce datasets from Tmall.com show that our methods outperform the state-of-the-art approaches, consid-ering several commonly used ranking-oriented evaluation criteria.

Keywords： Recommender systems     Heterogeneous implicit feedback     Confidence     Collaborative filtering     E-commerce    

HTML PDF Collect

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: User-generated content (UGC) such as blogs and twitters are exploding in modern Internet services. In such systems, recommender systems are needed to help people filter vast amount of UGC generated by other users. However, traditional rec-ommendation models do not use user authorship of items. In this paper, we show that with this additional information, we can significantly improve the performance of recommendations. A generative model that combines hierarchical topic modeling and matrix factorization is proposed. Empirical results show that our model outperforms other state-of-the-art models, and can provide interpretable topic structures for users and items. Furthermore, since user interests can be inferred from their productions, rec-ommendations can be made for users that do not have any ratings to solve the cold-start problem.

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

HTML PDF Collect

IN2CLOUD: A novel concept for collaborative management of big railway data

Jing LIN, Uday KUMAR

Frontiers of Engineering Management 2017, Volume 4, Issue 4,   Pages 428-436 doi: 10.15302/J-FEM-2017048

Abstract: address this challenge: 1) A hybrid cloud, 2) an intelligent cloud with hybrid cloud learning, and 3) collaborativeIN2CLOUD will help the movement of railway industry systems from “local” to “global” optimization in a collaborative

Keywords： railway     intelligent asset management     collaborative learning     big data     hybrid cloud     Bayesian    

HTML PDF Collect

ApproximateGaussian conjugacy: parametric recursive filtering under nonlinearity,multimodality, uncertainty Review

Tian-cheng LI, Jin-ya SU, Wei LIU, Juan M. CORCHADO

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 12,   Pages 1913-1939 doi: 10.1631/FITEE.1700379

Abstract: Since the landmark work of R. E. Kalman in the 1960s, considerable efforts have been devoted to time series state space models for a large variety of dynamic estimation problems. In particular, parametric filters that seek analytical estimates based on a closed-form Markov–Bayes recursion, e.g., recursion from a Gaussian or Gaussian mixture (GM) prior to a Gaussian/GM posterior (termed ‘Gaussian conjugacy’ in this paper), form the backbone for a general time series filter design. Due to challenges arising from nonlinearity, multimodality (including target maneuver), intractable uncertainties (such as unknown inputs and/or non-Gaussian noises) and constraints (including circular quantities), etc., new theories, algorithms, and technologies have been developed continuously to maintain such a conjugacy, or to approximate it as close as possible. They had contributed in large part to the prospective developments of time series parametric filters in the last six decades. In this paper, we review the state of the art in distinctive categories and highlight some insights that may otherwise be easily overlooked. In particular, specific attention is paid to nonlinear systems with an informative observation, multimodal systems including Gaussian mixture posterior and maneuvers, and intractable unknown inputs and constraints, to fill some gaps in existing reviews and surveys. In addition, we provide some new thoughts on alternatives to the first-order Markov transition model and on filter evaluation with regard to computing complexity.

Keywords： Kalman filter     Gaussian filter     Time series estimation     Bayesian filtering     Nonlinear filtering     Constrainedfiltering     Gaussian mixture     Maneuver     Unknown inputs    

HTML PDF Collect

Collaborative adoption of blockchain technology: A supply chain contract perspective

Frontiers of Engineering Management   Pages 121-142 doi: 10.1007/s42524-022-0239-8

Abstract: The outbreak of COVID-19 has significantly affected the development of enterprises. In the post-pandemic era, blockchain technology has become one of the important technologies to help enterprises quickly gain market competitiveness. The heavy investment required of supply chain stakeholders to employ blockchain technology has hindered its adoption and application. To tackle this issue, this study aims to facilitate the adoption of blockchain technology in a supply chain consisting of a core enterprise and a small/medium-sized enterprise through an effective supply chain contract. We analyze the performance of a cost-sharing (CS) contract and a revenue-sharing (RS) contract and propose a new hybrid CS-RS contract for better performance. We conduct comparative analyses of the three contracts and find that the hybrid CS-RS contract can more effectively incentivize both parties to reach the highest level of blockchain technology adoption and achieve supply chain coordination.

Keywords： blockchain     collaborative adoption     cost sharing     revenue sharing     hybrid contract    

HTML PDF Collect

Ion beam figuring of continuous phase plates based on the frequency filtering process

Mingjin XU,Yifan DAI,Xuhui XIE,Lin ZHOU,Shengyi LI,Wenqiang PENG

Frontiers of Mechanical Engineering 2017, Volume 12, Issue 1,   Pages 110-115 doi: 10.1007/s11465-017-0430-5

Abstract: This study proposes a multi-pass IBF approach with different beam diameters based on the frequency filteringWe present the selection principle of the frequency filtering method, which incorporates different removalA high-precision surface can be obtained as long as the filtering frequency is suitably selected.

Keywords： beam figuring (IBF)     continuous phase plates (CPPs)     machining accuracy     machining efficiency     frequency filtering    

HTML PDF Collect

Study on affecting factors of collaborative product development based on collaboration hierarchy model

ZHANG Xiaodong, LI Yingzi, ZHANG Zhiqiang

Frontiers of Mechanical Engineering 2007, Volume 2, Issue 2,   Pages 210-213 doi: 10.1007/s11465-007-0036-4

Abstract: Aiming at the levels of collaborative degree in web-based product development, a collaboration hierarchyThe application shows that it can solve the diverse problems of collaborative product development effectively

Keywords： development     web-based     business     collaborative     collaboration hierarchy    

HTML PDF Collect

Collaborative learning via social computing None

Ricardo S. ALONSO, Javier PRIETO, Óscar GARCÍA, Juan M. CORCHADO

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 2,   Pages 265-282 doi: 10.1631/FITEE.1700840

Abstract: One attractive challenge within educational innovation is the design of collaborative learning activitiesIn this paper, we present and evaluate context-aware framework for collaborative learning applicationsCAFCLA is a flexible framework that covers the entire process of developing collaborative learning activitiesIts application in the experimental case study of a collaborative WebQuest within a museum has shown

Keywords： Context-awareness     Collaborative learning     Social computing     Virtual organizations     Wireless sensor networks    

HTML PDF Collect

Filtering antennas: from innovative concepts to industrial applications Review Articles

Yun-fei CAO, Yao ZHANG, Xiu-yin ZHANG

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 1,   Pages 116-127 doi: 10.1631/FITEE.1900474

Abstract: A filtering antenna is a device with both filtering and radiating capabilities.The filtering antenna designs include single- and dual-polarized filtering patch antennas, a single-polarizedomni-directional filtering dipole antenna, and a dual-polarized filtering dipole antenna for the baseThe filtering antennas in this paper feature an innovative concept of eliminating extra filtering circuitsFor each design, the filtering structure is finely integrated with the radiators or feeding lines.

Keywords： Filtering antenna     Dual-band     Antenna array    

HTML PDF Collect

Basic model study on efficiency evaluation in collaborative design work process

XIE Qiu, YANG Yu, LI Xiaoli, ZHAO Ningyu

Frontiers of Mechanical Engineering 2007, Volume 2, Issue 3,   Pages 344-349 doi: 10.1007/s11465-007-0060-4

Abstract: During the efficiency evaluation process of collaborative design work, because of the lack of efficiencyevaluation models, a basic analytical model for collaborative design work efficiency evaluation is proposedFirst, the characteristics of the networked collaborative design system work process were studied; thenThis model, which is built for centralized collaborative design work, includes an analytical frame, a

Keywords： function     system work     evaluation process     efficiency evaluation     design work    

HTML PDF Collect

Title Author Date Type Operation

Preference transfer model in collaborative filtering for implicit data Project supported by

Bin JU,Yun-tao QIAN,Min-chao YE

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

Toward Privacy-Preserving Personalized Recommendation Services

Cong Wang, Yifeng Zheng, Jinghua Jiang, Kui Ren

Journal Article

A new item-based deep network structure using a restricted Boltzmann machine for collaborative filtering

Yong-ping DU, Chang-qing YAO, Shu-hua HUO, Jing-xuan LIU

Journal Article

An application of game theory in distributed collaborative decision making

Angran XIAO

Journal Article

A novel confidence estimation method for heterogeneous implicit feedback

Jing WANG, Lan-fen LIN, Heng ZHANG, Jia-qi TU, Peng-hua YU

Journal Article

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

IN2CLOUD: A novel concept for collaborative management of big railway data

Jing LIN, Uday KUMAR

Journal Article

ApproximateGaussian conjugacy: parametric recursive filtering under nonlinearity,multimodality, uncertainty

Tian-cheng LI, Jin-ya SU, Wei LIU, Juan M. CORCHADO

Journal Article

Collaborative adoption of blockchain technology: A supply chain contract perspective

Journal Article

Ion beam figuring of continuous phase plates based on the frequency filtering process

Mingjin XU,Yifan DAI,Xuhui XIE,Lin ZHOU,Shengyi LI,Wenqiang PENG

Journal Article

Study on affecting factors of collaborative product development based on collaboration hierarchy model

ZHANG Xiaodong, LI Yingzi, ZHANG Zhiqiang

Journal Article

Collaborative learning via social computing

Ricardo S. ALONSO, Javier PRIETO, Óscar GARCÍA, Juan M. CORCHADO

Journal Article

Filtering antennas: from innovative concepts to industrial applications

Yun-fei CAO, Yao ZHANG, Xiu-yin ZHANG

Journal Article

Basic model study on efficiency evaluation in collaborative design work process

XIE Qiu, YANG Yu, LI Xiaoli, ZHAO Ningyu

Journal Article