检索结果-内蒙古大学图书馆

Knowledge Graph-Enhanced Recommendation with Box Embeddings 23

23rd Chinese National Conference on Computational Linguistics, CCL 2024

作者： Liang, Qiuyu Wang, Weihua Lv, Lei Bao, Feilong College of Computer Science Inner Mongolia University Hohhot China National and Local Joint Engineering Research Center of Intelligent Information Processing Technology for Mongolian Hohhot China Inner Mongolia Key Laboratory of Mongolian Information Processing Technology Hohhot China

ISBN: (纸本)9780000000002

Knowledge graphs are used to alleviate the problems of data sparsity and cold starts in recommendation systems. However, most existing approaches ignore the hierarchical structure of the knowledge graph. In this paper, we propose a box embedding method for knowledge graph-enhanced recommendation system. Specifically, the box embedding represents not only the interaction between the user and the item, but also the head entity, the tail entity and the relation between them in the knowledge graph. Then the interaction between the item and the corresponding entity is calculated by the multi-task attention unit. Experimental results show that our method provides a large improvement over previous models in terms of Area Under Curve (AUC) and accuracy in publicly available recommendation datasets with three different domains. © 2024 China National Conference on Computational Linguistics.

关键词： Knowledge graph

来源：评论

学校读者我要写书评

暂无评论

Semantic Maximum Relevance and Modal Alignment for Cross-Modal Retrieval 11

Semantic Maximum Relevance and Modal Alignment for Cross-Mod...

引用

11th International Conference on Computing and Pattern Recognition, ICCPR 2022

作者： Sun, Pingping Qiang, Baohua Liu, Zhiguang Yang, Xianyi Xi, Guangyong Liu, Weigang Chen, Ruidong Zhang, Shihao Guilin University of Electronic Technology China The 54th Research Institute of Cetc Hebei Key Laboratory of Intelligent Information Perception and Processing China

ISBN: (纸本)9781450397056

With the increasing abundance of multimedia data resources, researches on mining the relationship between different modalities to achieve refined cross-modal retrieval are gradually emerging. In this paper, we propose a novel Semantic Maximum Relevance and Modal Alignment (SMR-MA) for Cross-Modal Retrieval, which utilizes the pre-trained model with abundant image text information to extract the features of each image text, and further promotes the modal information interaction between the same semantic categories through the modal alignment module and the multi-layer perceptron with shared weights. In addition, multi-modal embedding is distributed to the normalized hypersphere, and angular edge penalty is applied between feature embedding and weight in angular space to maximize the classification boundary, thus increasing both intra-class similarity and inter-class difference. Comprehensive analysis experiments on three benchmark datasets demonstrate that the proposed method has superior performance in cross-modal retrieval tasks and is significantly superior to the state-of-the-art cross-modal retrieval methods. © 2022 ACM.

关键词： Alignment

来源：评论

学校读者我要写书评

暂无评论

Research on Collaborative Filtering Algorithm of E-commerce Based on Flink 13

Research on Collaborative Filtering Algorithm of E-commerce ...

引用

13th International Conference on intelligent Control and information processing, ICICIP 2025

作者： Zheng, Haohao Luo, Xiaonan Zhu, Xiaoshu School of Computer Science and Information Security Guilin University of Electronic Technology Guilin China Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin China

ISBN: (纸本)9798331516147

In online shopping, a person's interest in a product is closely related to whether they will purchase it Analyzing people's interest in various products on time, along with product recommendations, can increase purchase rates. However, in many cases, We only know user implicit feedback, such as browsing or favoriting items, and cannot directly access user explicit feedback, such as product ratings. Moreover, users have limited exposure to products, resulting in a sparse user- item matrix. The traditional Alternating Least Squares (ALS) algorithm can partially address the issue of matrix sparsity, but its accuracy in recommending products based on implicit feedback alone is insufficient This paper proposes an improved ALS algorithm that converts implicit feedback into explicit ratings. We calculate the browsing frequency of a product based on user browsing counts. For a given product, we represent user preference by summing the browsing frequencies of all products with browsing frequencies less than or equal to that of the product. Then, by multiplying the preference level by the product's maximum rating, we derive a product rating, achieving a transformation from implicit feedback to explicit scores. Additionally, traditional collaborative filtering algorithms often use offline data, which may not align with user current preferences. To improve the algorithm's accuracy, we also utilize Flink for real-time data processing, allowing us to capture the most recent feedback data. This study tests the approach using the UserBehavior dataset from the publicly available Tianchi dataset. Experimental results indicate improvements in both Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). © 2025 IEEE.

关键词： Collaborative filtering

来源：评论

学校读者我要写书评

暂无评论

Lightweight improvement and global channel pruning tomato seedling grading model based on lightweight improvement and global channeling 3

Lightweight improvement and global channel pruning tomato se...

引用

3rd International Conference on Electronic information Engineering and Data processing, EIEDP 2024

作者： Zhao, Xiaoyan Fang, Jiandong Zhao, Yudong School of Information Engineering Inner Mongolia University of Technology Hohhot China Key Laboratory of Perception Technology Intelligent System of Inner Mongolia Autonomous Region Hohhot China Collaborative Innovation Center of perception Technology in Intelligent Agriculture and Animal Husbandry Inner Mongolia Autonomous region China Ulanqab Open University Ulanqab China

ISBN: (纸本)9781510680531

To achieve automatic grading of potting seedlings, improve performance, and reduce complexity, we collected and constructed a grading dataset using tomato potting seedlings as the test subject. We selected the YOLOv5n target detection model as the baseline model. We reduced the number of model parameters through lightweight improvements, integrated the similarity-based attention mechanism into the backbone network, enhanced the accuracy of potting seedling feature recognition by improving the CIOU loss function to EIOU, and performed global channel pruning on the improved model to further reduce its complexity. Experiments demonstrate the following results: the final model achieves a recall of 92.1%, an average precision mean of 94.9%, has 0.9×106M parameters, performs 2.1G floating-point operations, has a model weight size of 2.2M, and achieves a detection speed of 130 frames per second. Deployment and testing on edge devices confirm that the model achieves low computational requirements, has a small parameter count, maintains fast and accurate performance, and can be used for real-time classification of potting seedlings. © 2024 SPIE.

关键词： Grading

来源：评论

学校读者我要写书评

暂无评论

Enhancing Hindi Feature Representation Through Fusion of Dual-Script Word Embeddings 30

Enhancing Hindi Feature Representation Through Fusion of Dua...

引用

Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Wang, Lianxi Tian, Yujia Chen, Zhuowei School of Information Science and Technology Guangdong University of Foreign Studies Guangzhou510006 China Guangzhou Key Laboratory of Multilingual Intelligent Processing Guangzhou510006 China

ISBN: (纸本)9782493814104

Pretrained language models excel in various natural language processing tasks but often neglect the integration of different scripts within a language, constraining their ability to capture richer semantic information, such as in Hindi. In this work, we present a dual-script enhanced feature representation method for Hindi. We combine single-script features from Devanagari and Romanized Hindi Roberta using concatenation, addition, cross-attention, and convolutional networks. The experiment results show that using a dual-script approach significantly improves model performance across various tasks. The addition fusion technique excels in sequence generation tasks, while for text classification, the CNN-based dual-script enhanced representation performs best with longer sentences, and the addition fusion technique is more effective for shorter sequences. Our approach shows significant advantages in multiple natural language processing tasks, providing a new perspective on feature representation for Hindi. Our code has been released on https://***/JohnnyChanV/Hindi-Fusion. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Advancing Medical Imaging: A Domain-Adaptive Approach to Distinguish Lung Cancer and Pulmonary Cryptococcosis 46

Advancing Medical Imaging: A Domain-Adaptive Approach to Dis...

引用

46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Gao, Huanlong Zhu, Borui Zhang, Shuai He, Xuelei Chen, Yanwei Northwest University School of Information Sciences and Technology Xi'an710127 China Xi'an Key Laboratory of Imaging Omics and Intelligent Perception China Hospital of Guangzhou Medical University Guangzhou China

ISBN: (纸本)9798350371499

Pulmonary cryptococcosis (PC) is a subacute or chronic visceral mycosis caused by Cryptococcus neoformans, a yeast. This infection typically affects the lungs and central nervous system, with symptoms associated with pneumonia, meningitis, or involvement of the skin, bones, or internal organs. Computed Tomography (CT) is an important investigation for cryptococcosis and other lung diseases. Radiologists determine whether the patient has pulmonary cryptococcosis or lung cancer based on CT findings and clinical symptoms. However, the CT manifestations of pulmonary cryptococcus and lung cancer are similar, which often leads to misdiagnosis and makes patients suffer. In this paper, we present a domain adaptive classification method for addressing domain differences between datasets from different sources. This method combines a channel attention mechanism with adversarial networks to alleviate domain differences and enhance the model's generalization ability. Specifically, the channel attention aims to increase sensitivity to key features and enhance feature representation. By incorporating domain adaptation functions, the source domain is integrated with the target domain to focus on capturing feature differences. We validated this approach on a clinical dataset and achieved excellent results. © 2024 IEEE.

关键词： Lung cancer

来源：评论

学校读者我要写书评

暂无评论

Self-powered sensor based on compressible ionic gel electrolyte for simultaneous determination of temperature and pressure

引用

InfoMat 2024年第7期6卷 62-75页

作者： Junjie Zou Yanan Ma Chenxu Liu Yimei Xie Xingyao Dai Xinhui Li Shuxuan Li Shaohui Peng Yang Yue Shuo Wang Ce-Wen Nan Xin Zhang State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Center of Smart Materials and Devices&International School of Materials Science and EngineeringWuhan University of TechnologyWuhanthe People's Republic of China Hubei Key Laboratory of Energy Storage and Power Battery School of MathematicsPhysics and Optoelectronic EngineeringHubei University of Automotive TechnologyShiyanthe People's Republic of China Information Materials and Intelligent Sensing Laboratory of Anhui Province Key Laboratory of Structure and Functional Regulation of Hybrid Materials of Ministry of EducationInstitutes of Physical Science and Information TechnologyAnhui UniversityHefeithe People's Republic of China State Key Lab of New Ceramics and Fine Processing School of Materials Science and EngineeringTsinghua UniversityBeijingthe People's Republic of China

The simultaneous detection of multiple stimuli,such as pressure and temperature,has long been a persistent challenge for developing electronic skin(eskin)to emulate the functionality of human ***,the demand for integrated power supply units is an additional pressing concern to achieve its lightweightness and ***,we propose a self-powered dual temperature–pressure(SPDM)sensor,which utilizes a compressible ionic gel electrolyte driven by the potential difference between MXene and Al *** SPDM sensor exhibits a rapid and timely response to changes in pressure-induced deformation,while exhibiting a slow and hysteretic response to temperature *** distinct response characteristics enable the differentiation of current signals generated by different stimuli through machine learning,resulting in an impressive accuracy rate of 99.1%.Furthermore,the developed SPDM sensor exhibits a wide pressure detection range of 0–800 kPa and a broad temperature detection range of 5–75C,encompassing the environmental conditions encountered in daily human *** dual-mode coupled strategy by machine learning provides an effective approach for temperature and pressure detection and discrimination,showcasing its potential applications in wearable electronics,intelligent robots,human–machine interactions,and so on.

关键词： e-skin gel electrolyte machine learning self-powered dual-mode sensor

来源：评论

学校读者我要写书评

暂无评论

Gradient-Based Differential kWTA Network With Application to Competitive Coordination of Multiple Robots

引用

IEEE/CAA Journal of Automatica Sinica 2022年第8期9卷 1452-1463页

作者： Mei Liu Xiaoyan Zhang Mingsheng Shang Long Jin School of Information Science and Engineering Lanzhou UniversityLanzhou 730000 State Key Laboratory of Tibetan Intelligent Information Processing and Application Xining 810016China Chongqing Key Laboratory of Big Data and Intelligent Computing Chongqing Institute of Green and Intelligent TechnologyChinese Academy of SciencesChongqing 400714China Shenzhen Research Institute Lanzhou UniversityShenzhen 518063China

Aiming at the k-winners-take-all(kWTA)operation,this paper proposes a gradient-based differential kWTA(GDk WTA)*** obtaining the network,theorems and related proofs are provided to guarantee the exponential convergence and noise resistance of the proposed GD-kWTA ***,numerical simulations are conducted to substantiate the preferable performance of the proposed network as compared with the traditional ***,the GD-k WTA network,backed with a consensus filter,is utilized as a robust control scheme for modeling the competition behavior in the multi-robot coordination,thereby further demonstrating its effectiveness and feasibility.

关键词： Consensus filter k-winners-take-all(kWTA) multirobot coordination noise resistance

来源：评论

学校读者我要写书评

暂无评论

Experiment on protection performance of plasma array to 6GHz high-power microwave

Experiment on protection performance of plasma array to 6GHz...

引用

2023 Advanced Fiber Laser Conference, AFL 2023

作者： Liu, Yang Lv, Shouye Li, Jinzhou Meng, Gang Liao, Shuai Shi, Jiaming Satellite Information Intelligent Processing and Application Research Laboratory Beijing Institute of Remote Sensing Information Beijing100192 China State Key Laboratory of Pulsed Power Laser Technology National University of Defense Technology Hefei230037 China

ISBN: (纸本)9781510677661

For purpose of the electromagnetic pulse (EMP) protection research, a double-layer barrier of cylindrical plasma array was designed, and its protective performance to 6GHz high-power microwave (HPM) was conducted experimentally. Combining the distribution of the discharge plasma array, the shielding effectiveness of the double-layer plasma on 6GHz HPM pulse was studied. The main research contents and conclusions are as follows: The transmission energy of HPM decreased as the increase of plasma electron density, indicating an improved protection effect, with both double-layer and single-layer plasma array. Besides, the results showed that the transmission attenuation of HPM in double-layer structure was greater than that in single-layer structure because of the interlayer reflection. In addition, an interesting phenomenon was discovered during the experiment, which was that the boundary plasma units had a significant impact on the HPM transmission. The shielding effect of HPM was better with opening seven plasma units than that with opening whole plasma array. Finally, the spectral characteristics and transmission coefficients of the HPM were presented by Fourier transform, and the results of the protective performance were consistent with the above-mentioned time-domain analysis. The experiment results in this paper are of great significance in protecting against HPM based on plasma. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Carrier concentration

来源：评论

学校读者我要写书评

暂无评论

3D measurement of scattering media based on self-supervised fringe domain transformation

3D measurement of scattering media based on self-supervised ...

引用

2024 International Conference on Optical and Photonic Engineering, icOPEN 2024

作者： Tan, Ji Niu, Haipeng Luo, Suofan Liu, Jia He, Zhaoshui School of Automation Guangdong University of Technology Guangzhou510006 China Guangdong University of Technology Key Laboratory for IoT Intelligent Information Processing and System Integration Ministry of Education Guangzhou510006 China

ISBN: (数字)9781510688117

ISBN: (纸本)9781510688100

The scattering media measurement for structured light techniques remains challenging due to the subsurface scattering that destroys fringe patterns and introduces phase error. Recently, deep learning has been successfully applied to fringe analysis. Unfortunately, collecting a large scale of labeled data is difficult, especially in scattering media measurement scenarios. Inspired by image style transfer, we proposed a high-precision scattering medium measurement method based on self-supervised fringe domain transformation. Specifically, by treating degraded fringe and ideal fringe as two pattern styles, a cycle generation strategy is developed to achieve fringe enhancement by translating between two fringe domains. Two generators and two discriminators are used to form cycle-consistency constraints for self-supervised learning with unpaired dataset. Additionally, we combine numerical and physical constraints to jointly optimize network parameters, effectively suppressing phase-shift errors and improving phase quality. Since the proposed approach eliminates the need for label data, it exhibits great potential for applying deep learning to scattering medium measurement. Experiments verify that our method can obtain high-quality 3D morphology of translucent objects. © 2025 SPIE.

关键词： Velocity measurement

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：