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28th International Conference on Database Systems for Advanced applications, DASFAA 2023

作者： Li, Aoran Zang, Yalei Wang, Yani Li, Bohan College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing211106 China Key Laboratory of Safety-Critical Software Ministry of Industry and Information Technology Beijing China National Engineering Laboratory for Integrated Aero-Space-Ground Ocean Big Data Application Technology Xi’an China

ISBN: (纸本)9783031306716

Sequential recommendation systems dynamically predict the users’ next behaviors from chronological historical records to provide more accurate recommendations. However, in many real-world scenarios, recommenders find it difficult to make recommendations for cold-start users who have limited interactions with items. To address this issue, existing methods utilize auxiliary information to capture user preferences, which have achieved performance improvement to some extent. But with the gradual awareness of personal privacy, external information becomes difficult to obtain. Therefore, we develop a novel model called Path-based sequential Recommender for cold-start users (PathRec). PathRec exploits the rich sequential dependencies within the interactive paths to give reasonable recommendations for cold-start users without additional external information. Specifically, (i) PathRec constructs the global graph to learn the representations of the items. (ii) Then, PathRec elaborately selects the sampled paths to derive the underlying dependencies of the cold-start sequence. (iii) Finally, PathRec provides rich and complementary information to user-item interactions by strongly coupling the paths to give suitable recommendations. Extensive experiments on three datasets demonstrate the effectiveness of PathRec. In particular, our model can adapt to the cold-start users and has potential interpretability for recommendations. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Recommender systems

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An Approach for Performance Calculation of AVS/RS in Multi-floor Workshop 3rd

An Approach for Performance Calculation of AVS/RS in Multi-f...

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3rd International Conference on Smart Manufacturing, Industrial and Logistics engineering, SMILE 2023 and the 7th Asian Conference of Management Science and applications, ACMSA 2023

作者： Liu, Xiaopeng Wu, Cuiying Zhang, Baolin Xi, An Chen, Xuanrui Ministry of Industry and Information Technology Key Laboratory of Industrial Software Engineering Application Technology China Electronic Product Reliability and Environmental Testing Research Institute Guangzhou510619 China School of Computer and Information Engineering Hanshan Normal University Guangdong Chaozhou521041 China

ISBN: (纸本)9789819701933

Warehouse management is an important part of the production process. As a result of the development of technology, more and more companies tend to use automated logistics technologies such as AVS/RS to handle the internal logistics of the production system. Especially in multi-floor workshops, the production process on each floor are connected with each other through AVS/RS. It is becoming more and more important to study the integration process of AVS/RS and multi-floor workshop production process. In this paper, an integrated queuing network model of multi-floor workshop and AVS/RS was established, and a calculation method of system performance index was proposed. The accuracy and efficiency of the proposed method are demonstrated by comparing the results with simulations from numerical experiments. The work of this article can provide a basis for the design of autonomous vehicle storage and retrieve systems in multi-floor workshop, and the calculation method can be used as the support of WMS technology base. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Floors

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An efficient group key agreement protocol with administrator 3

An efficient group key agreement protocol with administrator

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3rd International Conference on Internet of Things and Smart City, IoTSC 2023

作者： Fang, Qihao Zhang, Lei Zhang, Mingrui Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai200062 China Science and Technology on Communication Security Laboratory Chengdu610041 China Engineering Research Center of Software/Hardware Co-design Technology and Application Ministry of Education Shanghai200062 China

ISBN: (纸本)9781510666375

Group key agreement technology is one of the most popular solution to establish a reliable secure channel between communicating entities of a group. Group key agreement protocol with administrator (GKAA) can handle a large number of group operations in sequence to resolve disorder problem and it is widely used in practical applications. However, in most of existing protocol, the administrator has to compute materials for each participant in the group which brings huge calculate overhead. In this paper, we propose an efficient group key agreement protocol with Administrator. Our GKAA protocol is able to perform group operation in a high efficacy way with the help of a key tree. It is also flexible and scalable since it suits for any network communication environment like IoT, video meeting, social applications, etc. Our protocol satisfies the properties including forward secrecy, PCS and key control resistance. © 2023 SPIE.

关键词： Network security

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Practical privacy-preserving mixing protocol for Bitcoin 26

Practical privacy-preserving mixing protocol for Bitcoin

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26th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2023

作者： Chang, Qianqian Xu, Lin Zhang, Lei Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai200062 China Science and Technology on Communication Security Laboratory Chengdu610041 China Engineering Research Center of Software/Hardware Co-design Technology and Application Ministry of Education Shanghai200062 China

ISBN: (纸本)9798350331684

The privacy of Cryptocurrencies are of great concern in various fields. Researches has shown that pseudonyms, which are used in Bitcoin, only provide weak privacy. The privacy of users may be put at risk under deanonymization attacks. The exisiting schemes typically require a trusted-third party to achieve anonymity, however this usually faces a single-point fault. In addition, existing schemes suffer from high communication complexity and impracticality. This paper proposes a practical privacy-preserving mixing protocol for Bitcoin to achieve unlink-ability of input and output address of transactions. Compared to existing schemes, our protocol improves practicality. The communication complexity of our protocol is linearly related to the number of peers. Moreover, our protocol is scalable as it works not only for Bitcoin, but also for other cryptocurrencies. © 2023 IEEE.

关键词： Computational complexity

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NOFTrack: Efficient Multi-Object Tracking with a Speed Advantage

NOFTrack: Efficient Multi-Object Tracking with a Speed Advan...

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2024 International Symposium on Digital Home, ISDH 2024

作者： Jiang, Ming Ke, Jiehao Guo, Biao Metaverse Application Engineering Center Guilin University of Electronic Technology Guilin China School of Computer Science and Information Security Guilin University of Electronic Technology Guilin China Guilin University of Electronic Technology Guangxi Key Laboratory of Trusted Software Guilin China

ISBN: (纸本)9798331509873

In the field of multi-object tracking (MOT), accurately tracking the position and characteristics of targets is crucial. However, traditional methods often overlook detection results with low confidence, which can lead to the omission of targets and the fragmentation of trajectories. To overcome these challenges, we have introduced a novel NOF algorithm. This algorithm efficiently handles detection boxes through a tiered strategy, initially using an adaptive Kalman filter for preliminary matching, followed by a secondary screening of detection boxes with lower confidence, and a final stage for processing dubious detection results. This approach not only enhances the speed and accuracy of tracking but also performs exceptionally well when dealing with complex scenes. Moreover, it is capable of achieving high efficiency, with a rate of over 300 frames per second (FPS), ensuring the efficiency and precision of the tracking process. © 2024 IEEE.

关键词： Target tracking

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Attribute Enhanced Graph Attention Networks for Session-based Recommendation 11

Attribute Enhanced Graph Attention Networks for Session-base...

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11th International Conference on Advanced Cloud and Big Data, CBD 2023

作者： Xu, Yidan Wang, Ning Wu, Jiaqi Xu, Shuai Li, Bohan Nanjing University of Aeronautics and Astronautics Nanjing China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing China Natl. Engineering Laboratory for Integrated Aero-Space-Ground Ocean Big Data Application Technology Xi'an China

ISBN: (纸本)9798350345346

Session-based recommendation (SBR) aims to predict the next item that the anonymous users will interact with based on their short behavior sequence. However, most of the current approaches towards SBR only focus on modeling users' interest preferences based on a series of items, ignoring extra item attributes, i.e., the brand attribute. This paper proposes a novel approach, called the Attribute Enhanced Graph Attention Networks for Session-based Recommendation (AGSR), using the brand attribute to better model user preferences. Specifically, (i) AGSR constructs the session graph of the current session to capture the user's session-level item embedding;(ii) AGSR constructs the brand global graph to capture the brand-level item embedding and brand embedding;(iii) Based on the learned node embeddings, AGSR apply attention layers to extract users' interest and brand preferences. Finally, AGSR makes the recommendation based on item features and user interest and brand preferences, so as to provide better recommendations. Extensive experiments on three real-world datasets demonstrate the effectiveness of our approach. © 2023 IEEE.

关键词： Embeddings

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Multi-Task Neural Learning Architecture for End-to-End Identification of Helpful Reviews

Multi-Task Neural Learning Architecture for End-to-End Ident...

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International Conference on Advances in Social Network Analysis and Mining, ASONAM

作者： Miao Fan Yue Feng Mingming Sun Ping Li Haifeng Wang Jianmin Wang National Engineering Laboratory of Deep Learning Technology and Application China School of Software Engineering Tsinghua University

ISBN: (纸本)9781538660522

Helpful reviews play a pivotal role in recommending desirable goods and accelerating purchase decisions of customers in e-commercial services. Given a large proportion of product reviews with unknown helpfulness/unhelpfulness, the research on automatic identification of helpful reviews has drawn much attention in recent years. However, state-of-the-art approaches still rely heavily on extracting heuristic text features from reviews with domain-specific knowledge. In this paper, we first introduce a multi-task neural learning (MTNL) architecture for identifying helpful reviews. The end-to-end neural architecture can learn to reconstruct effective features upon the raw input of words and even characters, and the multi-task learning paradigm helps to make more accurate predictions of helpful reviews based on a secondary task which fits the star ratings of reviews. We also build two datasets containing helpful/unhelpful reviews from different product categories in Amazon, and compare the performance of MTNL with several mainstream methods on both datasets. Experimental results confirm that MTNL outperforms the state-of-the-art approaches by a significant margin.

关键词： Task analysis Feature extraction Encoding Semantics Training Computer architecture

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PSTeC: A location-time driven modelling formalism for probabilistic real-time systems 18th

PSTeC: A location-time driven modelling formalism for probab...

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18th International GI/ITG Conference on Measurement, Modelling and Evaluation of Computing Systems and Dependability and Fault Tolerance, MMB and DFT 2016

作者： He, Kangli Chen, Yixiang Zhang, Min Zhang, Yuanrui MoE Engineering Research Center for Software/Hardware Co-design Technology and Application East China Normal University Shanghai China Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China

ISBN: (纸本)9783319315584

Internet of Things (IoT) and Cyber-Physical Systems (CPS) have become important topics in both theory and industry. In some application domains, such as when specifying the behaviour of precision mechanics, we need to include features of spatial-temporal consistency. How to model probabilistic real-time systems in such domains is a challenge. This paper presents a modelling formalism, called PSTeC, for describing the behaviour of probabilistic real-time systems focusing on spatial-temporal consistency with nondeterministic, probabilistic and real-time aspects. The consistency restricts a process to start and finish at the required location and time. Communications between agents is specified by interactive actions. The language we propose is an extension of STeC, which is a specification language for location-aware real-time systems, adding probabilistic operations so as to support the incorporation of probabilistic aspects. We first give a formal definition of the syntax for PSTeC, then focus on the details of its operational semantics, which maps a PSTeC term onto a Probabilistic Spatial-Temporal Transition System (PSTTS) following the structured operational semantics style. A simple example demonstrates the expressiveness of PSTeC. © Springer International Publishing Switzerland 2016.

关键词： Semantics

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A proof system in PADS

A proof system in PADS

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10th International Colloquium on Theoretical Aspects of Computing, ICTAC 2013

作者： Yao, Xinghua Zhang, Min Chen, Yixiang MoE Engineering Research Center for Software/Hardware Co-design Technology and Application East China Normal University Shanghai China Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China

ISBN: (纸本)9783642397172

The PADS (Process Algebra for Demand and Supply) framework is an approach to model resource demand and supply for the formal analysis of hierarchical scheduling. Inspired by the demand relation in PADS, we propose a weak demand relation covering several cases which can not be described by a demand relation. And we explore some properties of weak demand relation which are similar to properties of demand relation. Especially, if two tasks are in a weak demand relation then their schedulabilities are closely related. Furthermore, we present a proof system for the weak demand relation in a decomposing-composing way, which helps to compare two tasks' schedulabilities. Finally, we prove that the proof system is sound and complete with respect to the semantic definition of weak demand relation. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Semantics

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Dimensionality reduction based on sparse representation classifier

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Journal of Computational Information Systems 2012年第9期8卷 3777-3783页

作者： Yin, Kai School of Computer and Information Engineering Key Laboratory of Changzhou Software Technology Research and Application Changzhou Institute of Technology Changzhou 213002 China

The sparse representation-based classifier (SRC) has been developed and shows great potential for pattern classification. This paper aims to gain a discriminative projection such that SRC achieves the optimum performance in the projected pattern space. We use the decision rule of SRC to steer the design of a dimensionality reduction method, which is coined the sparse representation classifier steered discriminative projection. This algorithm matches SRC optimally in theory. Experiments are done on the AR and extended Yale B face image databases, and results show the proposed method is more effective than other dimensionality reduction methods with respect to the sparse representation-based classifier. © 2011 by Binary Information Press.

关键词： Classification (of information)

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