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检索条件"机构=Beijing Key Laboratory on Integration and Analysis of Large-cale Stream Data"

共 139 条记录，以下是41-50 订阅

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Efficient Early Sparsification for Accelerating Solutions to the Traveling Salesman Problem 10

Efficient Early Sparsification for Accelerating Solutions to...

引用

10th International Conference on Fuzzy Systems and data Mining, FSDM 2024

作者： Jiang, Yonglu Xing, Hongyu Shi, Hanchen Wei, Zijing Yang, Zhongguo School of Information Science and Technology North China University of Technology Beijing China School of London Brunel North China University of Technology Beijing China Department of Mathematics Brunel University London London United Kingdom Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data North China University of Technology Beijing China

ISBN: (纸本)9781643685694

The Travelling Salesman Problem (TSP) is a well-established NP-hard problem, often tackled using heuristic algorithms. While state-of-the-art learning-driven approaches for TSP perform comparably to classical solvers when trained on trivially small instances, they struggle to generalize the learned policy to larger, practical-scale instances. Consequently, as the number of cities increases, the efficiency of these algorithms diminishes significantly. This paper focuses on the early elimination of non-advantageous edges while retaining advantageous ones, thereby accelerating the TSP solution. Our approach involves capturing the differential frequencies of various edges during the early stages of an intelligent evolutionary algorithm, which we term as "knowledge" derived from the evolutionary process. We then design effective features to characterize the similarities and differences between edges. Leveraging this "knowledge", we label edges as either advantageous or non-advantageous. By integrating the guidance of a predictor, we intervene in the intelligent evolutionary algorithm to sparsify the TSP graph, ultimately enhancing the TSP solution. Our method effectively prunes edges in TSP instances, preserving the optimal path while minimizing redundant edges. Experimental results demonstrate that our approach significantly improves both computational efficiency and solution quality on the TSP50 and TSP100 test sets compared to other models. This methodology offers a novel perspective by extracting and utilizing latent knowledge among edges, thereby enhancing the performance of intelligent evolutionary algorithms in solving the TSP. Our findings not only improve current methodologies but also encourage further exploration and development in related fields and practical applications. © 2024 The Authors.

关键词： Traveling salesman problem

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Context-Aware Online IoT Service Scheduling Approach in Cloud Environments 7

Context-Aware Online IoT Service Scheduling Approach in Clou...

引用

7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering

作者： Wang, Xinyu Li, Han Zhao, Yun School of Information Science and Technology North China University of Technology Beijing China Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data North China University of Technology Beijing China

ISBN: (纸本)9781510656437

IoT applications consist of a series of correlated IoT services. Compared with traditional services, IoT services have new features in distribution, dependency, security and dynamism, which pose new challenges to the assurance of performance for cloud-based IoT services. Service scheduling on the cloud is an effective approach to guarantee service performance. Taking into account the complex contextual information of IoT services, this paper proposes a Context-Aware Online IoT Service Scheduling Approach in Cloud Environments. First, based on the characteristics of IoT services, a description of the IoT service scheduling problem is given, including the constraints of transforming the contexts of IoT services into scheduling. Then, the service scheduling problem is mapped to a scheduling plan prediction problem based on a neural network approach. To verify the effectiveness of the method, two baseline algorithms were selected and simulated on the WorkflowSim platform together with the method proposed in this paper. In comparison, our method is found to have similar scheduling costs with the optimization method, but can improve the efficiency when generating the scheduling plan, which can better meet the demands of low time delay for online scheduling under the conditions of dynamic changes in IoT context. © 2022 SPIE. All rights reserved.

关键词： Scheduling

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Tour Guide Robot Based on large Language Model and User Behavior analysis

Tour Guide Robot Based on Large Language Model and User Beha...

引用

Artificial Intelligence and Computer Engineering (ICAICE), International Conference on

作者： Haoran Lin Jing Wang Yutong Zhan Yuan Zhang Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data School of Information Science and Technology North China University of Technology Beijing China

ISBN: (数字)9798331528911

ISBN: (纸本)9798331528928

With the continuous development of human-computer interaction technology, the applications of tour guide robots in scenarios such as museums and exhibition halls are becoming increasingly widespread. However, traditional tour guide robots primarily rely on predefined content and texts, as well as pre-planned routes, making it difficult to adjust in real-time based on the diverse needs and interests of different visitors. This limitation restricts interactivity and engagement. To address this issue, this paper proposes an intelligent tour guide robot system that integrates large language model and user behavior analysis technology, aimed at dynamically adjusting tour content by real-time perception of visitors' interests. This system leverages the natural language processing capabilities of large language model, along with user behavior analysis techniques, to provide visitors with a more personalized and interactive tour experience. Experimental validation shows that the proposed tour guide robot system can enhance the accuracy and proactivity of tour presentations, thereby increasing user engagement and the overall effectiveness of the tour.

关键词： Accuracy Robot kinematics large language models Knowledge based systems Semantics Systems architecture Gaze tracking Real-time systems User experience Natural language processing

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A Decentralized Runtime Environment for Service Collaboration: The Architecture and a Case Study

A Decentralized Runtime Environment for Service Collaboratio...

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2021 IEEE World Congress on Services, SERVICES 2021

作者： Gao, Jing Wang, Guiling Yang, Zhongguo Zhao, Zhuofeng North China University Of Technology Beijing Key Laboratory On Integration And Analysis Of Large-scale Stream Data Beijing China

ISBN: (纸本)9781665427197

In this paper, we describe PACOL (Panoramic-Collaboration), a decentralized and multi-layered architecture of runtime environment for service collaboration. We illustrate by a case study why it is designed as a decentralized control architecture, and why it is designed to support multi-tenants and service solution evolution and continuous optimization. Preliminary case analysis indicates that PACOL could be a feasible proposition to realise cross-domain, reliable and optimized service collaboration for service collaboration towards Internet of Services. © 2021 IEEE.

关键词： Optimization

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Research on Construction Method of Science and Technology Service Domain Knowledge Map

Research on Construction Method of Science and Technology Se...

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IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)

作者： Jiaqi Qian School of Information Science and Technology North China University of Technology Beijing China Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data Beijing China

With the development of the science and technology service industry, there is an urgent need to effectively organize multi-source and heterogeneous science and technology resources to meet the personalized needs of science and technology services in different industrial fields, that is, to provide various services to different industrial fields according to industry perspectives. Required scientific and technological resources, including scientific and technological project resources and scientific and technological consulting resources, etc. Effective organization and management of scientific and technological resources can be completed by building a domain knowledge map for industrial industry scientific and technological services. However, these resource fields have a large number of data types, are highly professional, and have complex businesses. How to obtain useful data, information, and business knowledge from massive data and store it in a graph database to complete the construction of a knowledge graph is the subject of this article. Concerns. Therefore, this article proposes a set of methods that integrate data preprocessing and knowledge modeling based on structured data processing and ontology technology to complete the construction of domain knowledge graphs.

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MGeohash:Trajectory data index method based on historical data pre-partitioning 7

MGeohash:Trajectory data index method based on historical da...

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7th International Conference on Big data Computing and Communications, BigCom 2021

作者： Li, Zhengyu Zhao, Zhuofeng North China University of Technology Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data China

ISBN: (纸本)9781665442527

In recent years, the widespread use of mobile terminal equipment with positioning functions has generated a large-scale trajectory data set. It brings great challenges to the storage and query of trajectory data. Existing trajectory data indexing methods rarely consider the characteristics of uneven data distribution, a spatio-temporal index method based on historical data pre-partitioning is proposed which use the similarity of the trajectory data distribution in time and space, pre-partitioning the Geohash Code and designing the index storage model based on HBase. Compared with the HGrid and ST- Hash method, it effectively reduces the number of sub-queries during query, and improves the spatiotemporal query performance of trajectory data. © 2021 IEEE.

关键词： Digital storage

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Research on User Demand-Driven Service Matching Methodology 6

Research on User Demand-Driven Service Matching Methodology

引用

6th IEEE International Conference on Cloud Computing and Big data Analytics, ICCCBDA 2021

作者： Zhang, Huiying Yang, Dongju Beijing Key Laboratory on Integration and Analysis of Large-scale Stream Data North China University of Technology Beijing China

ISBN: (纸本)9780738105338

Services have seen a spike, and thus, how to accurately identify the needs of the users and match them with the appropriate services becomes the key to the research of service matching. Service matching involves a lot of work, of which the existing methods to complete the matching mainly depend on semantic similarity while the information of the service function is rarely taken into consideration. To solve the problem above, a user demand-driven method will be introduced. Based on the original service model, the user demand model is established, which aims at the actual needs of users. To cope with incomplete and inaccurate expressions of users' demands, the UserCF is applied to matching the similar needs of users so that the tag set is generated, making the user service tag information complete and modified;the LMIA is recommended to match the classified demands of users level by level with the purpose of weighted fusion. In the analysis of living examples, it is suggested that the method is more feasible than workable than the existing methods of service matching, and meanwhile, an 5.3% higher precision are obtained. © 2021 IEEE.

关键词： Semantics

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A data-driven Exploratory Service Composition Tool for data Scientists

A Data-driven Exploratory Service Composition Tool for Data ...

引用

2021 IEEE World Congress on Services, SERVICES 2021

作者： Chen, Gaojian Wang, Jing Li, Qianwen Yuan, Yunjing North China University Of Technology Beijing Key Laboratory On Integration And Analysis Of Large-Scale Stream Data Beijing China

ISBN: (纸本)9781665427197

In the era of big data, data scientists gain insights from data and make decisions. However, when constructing a data analysis pipeline, data scientists are often required to be proficient in multiple algorithm models and theoretical foundations, and they have to select and combine multiple algorithm models, and repeatedly adjust algorithms and parameters to construct a high-performance data analysis pipeline. In response to the above problems, this paper proposes an exploratory service composition tool, which can perform real-time service recommendations according to users' needs and data features, and assists users in constructing data analysis pipelines in an exploratory manner. This method can reduce the difficulty of data analysis, effectively save labor costs, and improve the quality and efficiency of data analysis. © 2021 IEEE.

关键词： Reinforcement learning

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An Intent Understanding and Entity Extraction Method Based on Intent-Slot Attention Mechanism

An Intent Understanding and Entity Extraction Method Based o...

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Electronic Information Engineering and Computer Science (EIECS), 2021 International Conference on

作者： Sheng-Yuan Cao Chen Liu Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data School of Information North China University of Technology Beijing China

In the realm of chronic disease health dialog, natural language understanding plays a pivotal role. It encompasses two vital subtasks: recognizing user intentions and populating relevant data slots. To establish a symbiotic relationship between these intentions and slots, fostering semantic-level modeling, we present an innovative algorithm for comprehending medical consultation intentions and extracting pertinent entities. This algorithm leverages an intention-slot attention mechanism. Our approach introduces a slot pick-through mechanism, which effectively captures the explicit connection between user intent and data slots. Furthermore, we have designed an intent-slot attention mechanism layer and devised a method for embedding contextual intent information into data slots in the form of intent label vectors. In conclusion, our experimental results, evaluated on the MedDG dataset, demonstrate the superiority of our proposed algorithm over other comparative methods. We achieve an accuracy rate of 78.1% for medical intent recognition, an F1 value of 94.9% for semantic slot-filling, and a sentence-level semantic framing accuracy of 73.2%.

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Meta-process: A noval approach for decentralized execution of process

Meta-process: A noval approach for decentralized execution o...

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2021 CCF International Conference on Service Science, ICSS 2021

作者： Fang, Lei Yang, Zhongguo Qin, Shenghui Zhang, Mingzhu Ali, Sikandar Zhao, Zhuofeng North China University of Technology Beijing Key Laboratory on Integration and Analysis of Large-cale Stream Data Beijing China China University of Petroleum Department of Computer Science and Technology Beijing China

ISBN: (纸本)9781665440455

With the rapid growth of internet usage for enterprise-wide and cross-enterprise business applications (such as those in Electronic Commerce), workflow systems are gaining importance as an infrastructure for automating inter-organizational interactions. However, the traditional centralized workflow management technology can no longer meet the needs of current application services. For example, in e-commerce, cross-enterprise business applications may cause many security problems and cross-domain problems in the implementation of workflow. At the same time, due to the uncertainty and variability of environment and user requirements in practical applications, many business logics are difficult to be completely defined in advance. Therefore workflow models need to be immediately built or adjusted dynamically. Nowadays, distributed scheduling and decentralized control of workflow have become the emerging trend and are facing many challenges at the forefront of Internet development technology. In this paper, a distributed workflow control execution method based on 'meta-process' is proposed. Specifically, we designed and implemented a decentralized distributed scheduling management system for workflow tasks. To manage and control the distributed scheduling of workflow, we constructed a 'meta-process', which can ensure the integrity of the control chain in the distributed scheduling process. Our system can efficiently handle the data state migration between task nodes and supports the dynamic adjustment of the workflow model. For validation, we simulated a large number of service scheme samples and applied them to the system, which proved that all service cases can be executed correctly. Therefore, the feasibility of this method is verified. © 2021 IEEE.

关键词： Electronic commerce

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