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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Ya-Bo Liu Da-You Liu Hong Qi Fang-Ming Gu College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China

ISBN: (纸本)0780384032

Both item-associations and user-associations mined from the rating table can be used to make personalized recommendation for the current user in rule-based recommend technique. Mining user-associations is the key for the recommendation based on user-associations. We find that the current user not only can be used to constrain the rule form in user-associations mining process, but also can be used to partition the rating table into two parts in order to accelerate user-associations mining. It is first proved that user-associations about the current user mined from the whole rating table are contained in those mined only from the data set that contain the current user's rating. Then, a user-association mining frame based on two-stage count called TSCF is proposed. TSCF frame can be implemented by using existing algorithms for mining association rules. And an algorithm TSCF-CL for mining user-associations is implemented by using the concept lattice. Last the performance comparison with ASARM algorithm shows that TSCF-CL can reach better time capacity.

关键词： Data mining Association rules Recommender systems Lattices Acceleration Filtering Computer science Educational technology Laboratories knowledge engineering

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A lifecycle-based parallel model of workflow management

A lifecycle-based parallel model of workflow management

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Wan-Jun Yu Da-You Liu Bo Yang Quan Liu College of Computer Science & Technology JiLin University Changchun China Key Laboratory of Symbolic Computation & Knowledge Engineering Ministry of Education Changchun China

ISBN: (纸本)0780384032

Workflow management systems (WFMSs) are used to coordinate and streamline business processes. Very large process instances are often running for a long period and the feedback iteration occurs frequently, thus the system is inefficient. To overcome such problems, we studied the issues that process modeling parallelly based on product lifecycle management and proposed a parallel model (LBPYYM: lifecycle-based parallel workflow model). First, the parallel process can be created with the model within a product lifecycle. Meanwhile, the complexity of process definition is reduced also by the parallel model. Second, the adhoc access control policies can be created in each phase of lifecycle to satisfy the access control requirement of the least privilege. Finally, two algorithms, which consist of 2-level role parse algorithm and 3-level role parse algorithm, are introduced. Through these two algorithms the workflow activities' participant can be defined very easily and flexibly.

关键词： engineering management Access control knowledge management Technology management Educational institutions Computer science Educational technology Laboratories knowledge engineering Computer science education

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A hybrid constraint propagation mechanism for resource-constrained scheduling

A hybrid constraint propagation mechanism for resource-const...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Ju-Yang Zhang Ji-Gui Sun College of Computer Science & Technology Jilin University Changchun China Key Laboratory for Symbolic Computation and Knowledge Engineering Ministry of Education Changchun China

ISBN: (纸本)0780384032

Handling resource constraints in resource-constrained scheduling is always a NP-hard problem. In the beginning of this paper, the overview of the approaches to managing resource constraints and the deficiency of them are shown. Then a hybrid mechanism based on CBA rules and resource energy forward checking is proposed. By applying this mechanism, the generality and the efficiency of our system are heightened.

关键词： Job shop scheduling Resource management Processor scheduling Programming profession Sun Educational institutions Computer science Educational technology Laboratories knowledge engineering

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Product lifecycle based on J2EE in PDM

Product lifecycle based on J2EE in PDM

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Wan-Jun Yu Da-You Liu Ni-Ya Li Quan Liu College of Computer Science & Technology JiLin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Changchun China

ISBN: (纸本)0780384032

PDM is an important technology of CIMS. The lifecycle management of PDM means that it is a process in which a product grows from conceptual generation, outline design to manufacture, maintenance, ultimately to be discarded as useless. This work introduces the background of PDM and the idea of PLM briefly; describes the hierarchy of the PDM; puts forward the architecture of PLM, the model of built-time and run-tune and the lifecycle service of state transition; finally, gives an example of PLM is given.

关键词： Project management Technology management Educational technology Computer integrated manufacturing Product design Pulse width modulation Educational institutions Computer science Laboratories knowledge engineering

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A modified particle swarm optimization for combining forecasting

A modified particle swarm optimization for combining forecas...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： X.Y. Feng L.M. Wan Y.C. Liang Y.F. Sun H.P. Lee Y. Wang Kollege of Computer Science and Technology Key Laboratory for Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China College of Computer Science and Technology Key Laboratory for Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun China The 8th Research Institute of Air Force Beijing China Institute of High Performance Computing Singapore Singapore

A modified particle swarm optimization (PSO) algorithm is proposed. Linear constraints in the PSO are added to satisfy the normalization conditions for different problems. A hybrid algorithm based on the modified PSO and combining forecasting is presented. Combining forecasting can improve the forecasting accuracy through combining different forecasting methods. The effectiveness of the algorithm is demonstrated through the prediction on the sunspots and the stocks data. Simulated results show that the hybrid algorithm can improve the forecasting accuracy to a great extent.

关键词： Particle swarm optimization computational modeling Computer science Educational technology Laboratories Military computing knowledge engineering Computer science education High performance computing Predictive models

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Feature selection and text classification for Chinese Web documents

Feature selection and text classification for Chinese Web do...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Jian-Chao Xu Da-You Liu Ming Hu Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China School of Computer Science & Engineering Changchun University of Science and Technology Changchun China

ISBN: (纸本)0780384032

A great deal of methods for feature selection and text classification have been widely applied to English Web documents, while few studies have been done on Chinese Web documents. This paper gives a term weighting method based on inverse document frequency, HTML tags and length of Chinese phrase, reports our method to select Web text feature based on the messy genetic algorithm, provides an algorithm for Web text classification based on improvement on lattice machine approach. Our experiments show that these methods are valuable.

关键词： Text categorization Web pages Frequency knowledge engineering Genetic algorithms Lattices HTML Computer science Educational technology Laboratories

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Searching for closed itemset with formal concept analysis

Searching for closed itemset with formal concept analysis

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Hong Qi Da-You Liu Cheng-Quan Hu Ming Lu Liang Zhao Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China Jilin University Changchun Jilin CN Coll. of Comput. Sci. & Technol. Jilin Univ. Changchun China College of Computer Science and Technology Jilin University Changchun China

ISBN: (纸本)0780384032

The problem of mining frequent patterns plays an essential role in many important data mining tasks. However, it often generates a very large number of frequent itemsets. The set of frequent closed itemsets uniquely determines the exact frequency of all itemsets, yet it can be orders of magnitude smaller than the set of all frequent itemsets. An algorithm Closearcher based on formal concept analysis for closed itemset searching is proposed. This algorithm divides the whole search space of closed itemsets into several subspaces in accordance with criterions prescribed ahead, and introduces an efficient scheme to recognize the valid ones, in which the search for closed itemsets is bounded. An intermediate structure is employed to judge the validity of a subspace and search closed itemsets more efficiently. The algorithm is experimental evaluated and compared with the famous NextClosure algorithm proposed by Ganter for random generated data, as well as for real application data. The results show that our algorithm performs much better than the later.

关键词： Itemsets Data mining Machine learning algorithms Pattern analysis Frequency Algorithm design and analysis Databases Educational institutions Computer science Educational technology

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MAINet: Modality-Aware Interaction Network for Medical Image Fusion

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ACM Transactions on Multimedia Computing, Communications, and Applications 1000年

作者： Lisi Wei Libo Zhao Xiaoli Zhang College of Computer Science and Technology Jilin University China College of Artificial Intelligence and Big Data Hulunbuir University China and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University China College of Computer Science and Technology Jilin University China and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University China

Due to the limitations of imaging sensors, obtaining a medical image that simultaneously captures both functional metabolic data and structural tissue details remains a significant challenge in clinical diagnosis. To address this, Multimodal Medical Image Fusion (MMIF) has emerged as an effective technique for integrating complementary information from multimodal source images, such as CT, PET, and SPECT, which is critical for providing a comprehensive understanding of both anatomical and functional aspects of the human body. One of the key challenges in MMIF is how to exchange and aggregate this multimodal information. This paper rethinks MMIF by addressing the harmony of modality gaps and proposes a novel Modality-Aware Interaction Network (MAINet), which leverages cross-modal feature interaction and progressively fuses multiple features in graph space. Specifically, we introduce two key modules: the Cascade Modality Interaction (CMI) module and the Dual-Graph Learning (DGL) module. The CMI module, integrated within a multi-scale encoder with triple branches, facilitates complementary multimodal feature learning and provides beneficial feedback to enhance discriminative feature learning across modalities. In the decoding process, the DGL module aggregates hierarchical features in two distinct graph spaces, enabling global feature interactions. Moreover, the DGL module incorporates a bottom-up guidance mechanism, where deeper semantic features guide the learning of shallower detail features, thus improving the fusion process by enhancing both scale diversity and modality awareness for visual fidelity results. Experimental results on medical image datasets demonstrate the superiority of the proposed method over existing fusion approaches in both subjective and objective evaluations. We also validated the performance of the proposed method in applications such as infrared-visible image fusion and medical image segmentation.

关键词： Multimodal fusion Medical image fusion Cascade modality interaction Modality-awareness Graph convolutional network

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Collaborative WSN-UAV Data Collection in Smart Agriculture: A Bi-objective Optimization Scheme

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ACM Transactions on Sensor Networks 1000年

作者： Geng Sun Xiaoya Zheng Jiahui Li Hui Kang Shuang Liang 1) College of Computer Science and Technology Jilin University 2) Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University China College of Computer Science and Technology Jilin University China College of Information Science and Technology Northeast Normal University China

Smart agriculture which integrates the agriculture with Internet of Things (IoT) has attracted attention since it contributes to increase the productivity and quality of crops, reduce energy consumption and facilitate the farmers. Wireless sensor networks (WSNs) and unmanned aerial vehicles (UAVs) are two most commonly deployed devices that are used for enabling the smart agriculture. In this paper, we design a collaborative WSN-UAV system, wherein different clusters of sensor nodes form different sensor-based virtual antenna arrays (SVAAs) to transmit the collected data towards different receiver UAVs via adopting collaborative beamforming (CB), then the receiver UAVs will take the collected data back to the ground control station (GCS). We formulate a transmission rate and battery energy bi-objective optimization problem (TRBEBOP) to simultaneously maximize the total transmission rate of the sensor-based CB clusters and the total remaining battery energy of the selected sensor nodes, by selecting appropriate sensor nodes in each cluster that can form a predominant SVAA, determining suitable receiver UAVs and optimizing the excitation current weights of the selected sensor nodes. To handle the formulated TRBEBOP that is demonstrated to be non-convex and NP-hard, an enhanced non-dominated sorting genetic algorithm II (ENSGA-II) with several specific designs is presented. Simulation results validate the effectiveness of the proposed ENSGA-II for solving the formulated TRBEBOP. Moreover, compared with other benchmark algorithms, the superiority of the proposed ENSGA-II is demonstrated. In addition, the impacts of several fortuitous circumstances on the system are estimated, and the results illustrate the robustness of the proposed scheme. Finally, the discussion about several mechanisms to deal with the interference induced by the sidelobe levels and the impact of UAV movement on receiving rate are provided.

关键词： Smart agriculture wireless sensor networks unmanned aerial vehicles collaborative beamforming multi-objective optimization problem.

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