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Proceedings of the 20th Web Information Systems and Applications Conference, WISA 2023

作者： Cui, Hengrui He, Jiaxing Zeng, Weixin Laboratory for Big Data and Decision National University of Defense Technology Changsha China

ISBN: (纸本)9789819962211

Policy-oriented object ranking is of great importance in the field of object recommendation and target retrieval, such as e-commerce recommendation system, financial services and selecting hosts of some large-scale sports events. However, the solution of such problem is often accompanied by the processing of massive high-dimensional data. The typical methods may lead to the phenomenon of over-reliance on historical data as well as ignoring the interactions among indicators. This also causes the ranking results to lose part of the timeliness and sensitivity. We designed Entropy-weighted Synthetic Model (ESM) in order to optimize the defects above. We focus on the case of Olympic Host Country or Region Selection to demonstrate the superiority of our method. We first fulfill calculation of synthetic property weights and differential data of each attribute based on time series of the selected synthetic group. Then we evaluate the weight of each indicator, obtain the comprehensive scores and generate the ranking results of the target countries or regions. Last, we implement Placebo Test to eliminate the effects of Synthetic Control Method (SCM) and validate the robustness of the model with the support of Hypothesis Test. From the perspective of comparing with the results of Difference-in-Difference Model (DID) and Propensity Score Matching (PSM), ESM shows better adaptability and predictability and provide conclusion consistent with professional perspective. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Entropy

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Field Named Entity Recognition Based on Double Layer Conditional Random Fields 9

Field Named Entity Recognition Based on Double Layer Conditi...

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9th International Conference on big data and Information Analytics, bigDIA 2023

作者： Wang, Tengyun Li, Hongfei Xiao, Kaiming Huang, Hongbin National University of Defense Technology Laboratory for Big Data and Decision Changsha China

ISBN: (纸本)9798350330076

Military named entities are the core information elements in military corpora and important processing objects in military field information processing. Named Entity Recognition (NER) has made significant progress, allowing for a higher level of recognition for simple military named entities. However, how to effectively identify nested military named entities from data containing a large number of nested military named entities remains a challenge. This article proposes a dual layer conditional random field (DLCRF) model to address the challenges of nested military named entity recognition tasks. Specifically, a two-layer conditional random field is constructed, where simple military places, simple military equipment, and simple military institutions are identified attheunderlying conditional random field. The results are then uploaded to the high-level conditional random field, where nested ilitary places, nested military equipment, and nested military institutions are identified. In addition, due to the limited number of publicly available military domain annotated datasets, this article constructed a annotated military news dataset containing a large number of nested military named entities and conducted experiments on the nested military named entity recognition task on this dataset. The results from the experiments indicate that this model exhibits notable strengths in performing nested military named entity recognition tasks, outperforming certain widely used deep learning neural networks. © 2023 IEEE.

关键词： Random processes

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STIOS: A Novel Self-supervised Diffusion Model for Trajectory Imputation in Open Environment Scenarios 17

STIOS: A Novel Self-supervised Diffusion Model for Trajector...

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IEEE Congress on Cybermatics: 17th IEEE International Conference on Internet of Things, iThings 2024, 20th IEEE International Conference on Green Computing and Communications, GreenCom 2024, 17th IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2024, 10th IEEE International Conference on Smart data, Smartdata 2024

作者： Hu, Zhijing Yan, Hao Zheng, Yuhao He, Hua Chen, Chao Fan, Changjun Huang, Kuihua National University of Defense Technology Laboratory for Big Data Data and Decision Changsha China Central South University School of Computer Science and Engineering Changsha China

ISBN: (纸本)9798350351637

With the growth of location-based services, the accumulation of large amounts of trajectory data comes with the challenge of missing data. Existing trajectory imputation methods rely on deterministic models that cannot take into account open environments scenarios without auxiliary information. This may lead to poor performance in learning the long-term dependencies of trajectories. In this paper, we propose a novel Self-supervised diffusion model for Trajectory Imputation in Open environment Scenarios (STIOS), which combines a deterministic model and a conditional diffusion model. In addition, we propose a self-supervised training method inspired by masked language modelling that divides the data into conditional information and estimation targets. Extensive experiments on two real datasets demonstrate the superiority of STIOS for trajectory imputation. © 2024 IEEE.

关键词： Self-supervised learning

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Unified Transformation Framework of Open Tag Feature for Chinese Multi-modal data 9

Unified Transformation Framework of Open Tag Feature for Chi...

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9th International Conference on big data and Information Analytics, bigDIA 2023

作者： Ge, Bin He, Chunhui Zhang, Chong Xu, Hao Hu, Shengze National University of Defense Technology Laboratory for Big Data and Decision Changsha410073 China

ISBN: (纸本)9798350330076

With the popularization of the Internet and the development of We Media, multi-modal data such as video, audio, image and text have become the mainstream forms of information dissemination. How to efficiently solve the representation heterogeneity problem of these multi-modal data has become a research hotspot. After studying a large amount of literature, it is found that the unified mapping of multi-modal data can be realized via text tags. In order to solve the problem of heterogeneous representation of multi-modal data, an open tag unified transformation framework for Chinese multi-modal data is proposed. This framework can use different conversion models for data of different modalities to convert them into text uniformly. High-quality multi-grained open text tags are then extracted from the above-mentioned converted texts using tag extraction algorithms. Finally, the data object corresponding to the source modality is mapped with the extracted text tags, so as to solve the transformation problem of unified tag feature of multi-modal data. The experimental results of each module can be fully explained that the technical feasibility of our framework, and provide a novel direction for feature transformation and representation of multi-modal data. © 2023 IEEE.

关键词： Information dissemination

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An Improved Apriori Algorithm Based on Goal Orientation and Double Pruning

An Improved Apriori Algorithm Based on Goal Orientation and ...

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2023 International Conference on Networks, Communications and Intelligent Computing, NCIC 2023

作者： Deng, Shiyu Li, Li Xiong, Yichen Zhang, Jian School of Computer Science Beijing International Science and Technology Cooperation Base of Intelligent Decision and Big Data Application Beijing Information Science and Technology University Laboratory of Big Data Decision Making for Green Development Beijing China School of Economics and Management Beijing International Science and Technology Cooperation Base of Intelligent Decision and Big Data Application Beijing Information Science and Technology University Laboratory of Big Data Decision Making for Green Development Beijing China

ISBN: (纸本)9798350371949

Aiming at solving the problem of high time complexity of association rule mining among item-sets in Apriori algorithm and obtaining the set of goal-association relations of single-to-single point type, this paper improves the Apriori algorithm based on Goal Orientation and Double Pruning (GODP-Apriori). Oriented by the type of goal, the GODP-Apriori uses double pruning to remove the redundant item set during the calculation of the frequency of item set support, which greatly improves the efficiency of obtaining the frequent item set;in addition to this, by sacrificing space for time, it also records the set of transaction items corresponding to the item when calculating the support degree, which avoids the repetitive scanning in the subsequent calculations and then effectively increases the computation efficiency of traditional Apriori algorithm. The effectiveness of GODP-Apriori algorithm in improving the calculation time efficiency of traditional Apriori algorithm was verified by using a real household electricity consumption data at the end of this research. © 2023 IEEE.

关键词： Association rules

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Spatiotemporal deformation analysis of glaciers and surrounding landscapes in the Shishapangma region using InSAR techniques

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Journal of Mountain Science 2025年第1期22卷 210-229页

作者： LIANG Wenli LIU Rui JI Qin KOU Pinglang Chongqing Key Laboratory of GIS Application School of Geography and TourismChongqing Normal UniversityChongqing 401331China National Earth System Science Data Center Beijing 100000China Chongqing Engineering Research Center of Spatial Big Data Intelligent Technology Chongqing University of Posts and TelecommunicationsChongqing 400065China Key Laboratory of Tourism Multisource Data Perception and Decision Ministry of Culture and Tourism(TMDPDMCT)Chongqing University of Posts and TelecommunicationsChongqing 400065China

Glacier dynamics in the Himalayan midlatitudes,particularly in regions like the Shishapangma,are not yet fully understood,especially the localized topographic and climatic impacts on glacier *** study analyzes the spatiotemporal characteristics of glacier surface deformation in the Shishapangma region using the Small Baseline Subset(SBAS)Interferometric Synthetic Aperture Radar(In SAR)*** analysis reveals an average deformation rate of-4.02±17.65 mm/yr across the entire study area,with glacier regions exhibiting significantly higher rates of uplift(16.87±13.20 mm/yr)and subsidence(20.11±14.55 mm/yr)compared to non-glacier *** identifies significant surface lowering on the mountain flanks and localized uplift in certain catchments,emphasizing the higher deformation rates in glacial areas compared to non-glacial *** found a strong positive correlation between temperature and cumulative deformation(correlation coefficient of 0.63),particularly in glacier areas(0.82).The research highlights the role of temperature as the primary driver of glacier wastage,particularly at lower elevations,with strong correlations found between temperature and cumulative *** also indicates the complex interactions between topographic features,notably,slope gradient,which shows a positive correlation with subsidence rates,especially for slopes below 35°.South-,southwest-,and west-facing slopes exhibit significant uplift,while north-,northeast-,and east-facing slopes predominantly ***,we identified transition zones between debris-covered glaciers and clean ice as areas of most intense deformation,with average rates exceeding 30 mm/yr,highlighting these as potential high-risk zones for *** study comprehensively analyzes the deformation characteristics in both glacier and non-glacier areas in the Shishapangma region,revealing the complex interplay of topographic,climatic,and hydrological factors influencing glacier dynamic

关键词： Glacier melting SBAS-InSAR Topographic factors Temperature change Middle Himalayas

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Dynamic-prototype Contrastive Fine-tuning for Continual Few-shot Relation Extraction with Unseen Relation Detection 31

Dynamic-prototype Contrastive Fine-tuning for Continual Few-...

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31st International Conference on Computational Linguistics, COLING 2025

作者： Zhao, Simiao Tan, Zhen Pang, Ning Xiao, Weidong Zhao, Xiang National Key Laboratory of Information Systems Engineering National University of Defense Technology China Laboratory for Big Data and Decision National University of Defense Technology China

ISBN: (纸本)9798891761964

Continual Few-shot Relation Extraction (CFRE) aims to continually learn new relations from limited labeled data while preserving knowledge about previously learned relations. Facing the inherent issue of catastrophic forgetting, previous approaches predominantly rely on memory replay strategies. However, they often overlook task interference in continual learning and the varying memory requirements for different relations. To address these shortcomings, we propose a novel framework, DPC-FT, which features: 1) a lightweight relation encoder for each task to mitigate negative knowledge transfer across tasks;2) a dynamic prototype module to allocate less memory for easier relations and more memory for harder relations. Additionally, we introduce the None-Of-The-Above (NOTA) detection in CFRE and propose a threshold criterion to identify relations that have never been learned. Extensive experiments demonstrate the effectiveness and efficiency of our method in CFRE, making our approach more practical and comprehensive for real-world scenarios. © 2025 Association for Computational Linguistics.

关键词： Knowledge transfer

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Multi-UAV Formation Obstacles Avoidance Path Planning Based on PPO Algorithm 9

Multi-UAV Formation Obstacles Avoidance Path Planning Based ...

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9th International Conference on big data and Information Analytics, bigDIA 2023

作者： Wan, Yu Zhao, Zipeng Tang, Jun Chen, Xi Qi, Jingtao National University of Defense Technology Laboratory for Big Data and Decision College of Systems Engineering Changsha China

ISBN: (纸本)9798350330076

The path planning of multi-UAV formations plays a crucial role in various scenarios, including rescue operations, reconnaissance missions, and target strikes. This paper investigates a method for multi-UAV formation obstacle avoidance route planning based on deep reinforcement learning. The proposed method allows UAVs to efficiently plan routes in complex and dynamic three-dimensional obstacle environments. The autonomous decision-making of multiple UAVs is realized by using the proximal policy optimization (PPO) algorithm. In addition, in order to achieve formation obstacle avoidance, we design a reward function to assess the advantages and disadvantages of UAV strategies. Finally, an environment with dynamic obstacles is constructed and trained using the method. Experimental results show that the method is feasible and generalizable. © 2023 IEEE.

关键词： Motion planning

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Semantic and Sentiment Dual-Enhanced Generative Model for Script Event Prediction 31

Semantic and Sentiment Dual-Enhanced Generative Model for Sc...

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31st International Conference on Computational Linguistics, COLING 2025

作者： Wu, Feiyang Huang, Peixin Hu, Yanli Tan, Zhen Zhao, Xiang Laboratory for Big Data and Decision National University of Defense Technology China National Key Laboratory of Information Systems Engineering National University of Defense Technology China

ISBN: (纸本)9798891761964

Script Event Prediction (SEP) aims to forecast the next event in a sequence from a list of candidates. Traditional methods often use pre-trained language models to model event associations but struggle with semantic ambiguity and embedding bias. Semantic ambiguity arises from the multiple meanings of identical words and insufficient consideration of event arguments, while embedding bias results from assigning similar word embeddings to event pairs with similar lexical features, despite their different meanings. To address above issues, we propose a the Semantic and Sentiment Dual-enhanced Generative Model (SSD-GM). SSD-GM leverages two types of script event information to enhance the generative model. Specifically, it employs a GNN-based semantic structure aggregator to integrate the event-centric structure information, thereby mitigating the impact of semantic ambiguity. Furthermore, we find that local sentiment variability effectively reduces biases in event embeddings, while maintaining global sentiment consistency enhances predictive accuracy. As a result, SSD-GM adeptly captures both global and local sentiment of events through its sentiment information awareness mechanism. Extensive experiments on the Multi-Choice Narrative Cloze (MCNC) task demonstrate that our approach achieves better results than other state-of-the-art baselines. © 2025 Association for Computational Linguistics.

关键词： Embeddings

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Microwave Signal Replicator Design for Testing of the Multi-Channel Transcranial Magnetic Stimulator

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International Journal of Crowd Science 2024年第2期8卷 83-87页

作者： Chen, Qiuju Zhang, Kai Pang, Jian Zhang, Shancai Feng, Guangyao Wu, Congfeng Li, Wei National Synchrotron Radiation Laboratory University of Science and Technology of China Hefei230029 China Laboratory for Big Data and Decision Hefei230027 China Advanced Manufacturing Engineering College Hefei University Hefei230601 China

The multi-channel transcranial magnetic stimulator is commonly used for rehabilitation treatment of ischemic cerebrovascular disease, neurosis, and brain injury diseases in the elderly. And multiple high coherency signals are required as inputs for its test, which are with consistent frequency, adjustable amplitude, equal magnitude, and long-time phase consistency ⩽±1°. But ordinary signal sources have only one output channel, which is far from meeting the test requirements. If the traditional power division is used for the duplication, the phase difference between the channels will be larger than ±1°. If the multi-throw Radio Frequency (RF) switch is used, it will seriously affect the phase consistency of the input signal and increase the distortion of the signal. In order to solve the above problems, the method to extend the output of the microwave signal source has been proposed in the paper by using the integrated transceiver AD9361. The proposed method can realize the duplication of the number of signal channels according to user requirements. Then a signal replicator has been designed by combining AD9361 chip and Field-Programmable Gate Array (FPGA) control module. The experimental platform has been built to test the performance of the designed device. Experimental results show that the duplicated signals are highly consistent with the source signal in the power amplitude and frequency, meanwhile the phase of the duplicated signals are all highly consistent with each other. © The author(s) 2024.

关键词： Field programmable gate arrays (FPGA)

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