International Journal of Machine Learning and Cybernetics OnlineFirst articles | Skip to main content

International Journal of Machine Learning and Cybernetics OnlineFirst articles

28-03-2023 | Original Article

Recommendation model based on multi-grained interaction that fuses users’ dynamic interests

Users leave many reviews while participating in network activities, and these have been proven to improve the performance of recommendation systems. However, most current works in the field of rating prediction only capture preference information …

Zhenyu Yang, Yu Wang, Guojing Liu, Zhe Li, Xingang Wang

28-03-2023 | Original Article

Link prediction for heterogeneous information networks based on enhanced meta-path aggregation and attention mechanism

Heterogeneous link prediction aims to reveal potential connections between two nodes in heterogeneous information networks. Most existing studies are based on meta-paths, but ignore the information contained in incomplete meta-paths. They simply …

Hao Shao, Lunwen Wang, Rangang Zhu

25-03-2023 | Original Article

RNON: image inpainting via repair network and optimization network

In the last few years, image inpainting methods based on deep learning models had shown obvious advantages compared with existing traditional methods. The former can better generate visually reasonable image structure and texture information.

Yuantao Chen, Runlong Xia, Ke Zou, Kai Yang

Open Access 25-03-2023 | Original Article

A unified approach to designing sequence-based personalized food recommendation systems: tackling dynamic user behaviors

The recommender system (RS) is a well-known practical application of the state-of-the-art information filtering and machine learning technologies. Traditional recommendation approaches, including collaborative and content-based filtering …

Jieyu Zhang, Zidong Wang, Weibo Liu, Xiaohui Liu, Qiusheng Zheng

25-03-2023 | Original Article

Deep hashing via multi-scale and multi-directional pooling for image retrieval

Deep Hashing methods have been widely used for large-scale image retrieval due to its advantages in retrieval efficiency and accuracy. Recent methods cannot effectively capture the scale variation and complex distribution of image features in the …

Yunbo Rao, Wang Zhou, Shaoning Zeng, Junmin Xue

23-03-2023 | Original Article

Text semantic matching with an enhanced sample building method based on contrastive learning

Text semantic matching aims to determine whether two pieces of text point to the same semantic, which has been widely applied in clinical terminology standardization, recommendation systems, and other scenarios. Recently, many existing methods …

Lishan Wu, Jie Hu, Fei Teng, Tianrui Li, Shengdong Du

22-03-2023 | Original Article

ESTI: an action recognition network with enhanced spatio-temporal information

Action recognition is an active topic in video understanding, which aims to recognize human actions in videos. The critical step is to model the spatio-temporal information and extract key action clues. To this end, we propose a simple and …

ZhiYu Jiang, Yi Zhang, Shu Hu

21-03-2023 | Original Article

Enhanced neighborhood node graph neural networks for load forecasting in smart grid

Deep learning technology creates the condition for the optimization of the smart grid, and the big data analytical technique has the most efficient way to analyze and share the power load spatio-temporal data in the smart grid. Utilizing the …

Jiang Yanmei, Liu Mingsheng, Li Yangyang, Liu Yaping, Zhang Jingyun, Liu Yifeng, Liu Chunyang

20-03-2023 | Original Article

NMEAS: Neuro-MaxEnt architecture search

Fusion operations are widely used in many hand-crafted convolutional neural network model to reduce parameter number and improve feature learning, however, most neural architecture search methods suffered from large search cost, usually used …

Zhiyuan Zou, Weibin Liu, Weiwei Xing, Shunli Zhang

19-03-2023 | Original Article

HMNet: a hierarchical multi-modal network for educational video concept prediction

Educational video concept prediction is a challenging task in the online education system that aims to assign appropriate hierarchical concepts to the video. The key to this problem is to model and fuse the multimodal information of the video.

Wei Huang, Tong Xiao, Qi Liu, Zhenya Huang, Jianhui Ma, Enhong Chen

18-03-2023 | Original Article

Importance-aware contrastive learning via semantically augmented instances for unsupervised sentence embeddings

Attaining better sentence embeddings benefits a wide range of natural language processing tasks. SimCSE applied a simple contrastive learning framework to train BERT models and achieved excellent sentence embeddings. Based on SimCSE, this paper …

Xin Ma, Hong Li, Jiawen Shi, Yi Zhang, Zhigao Long

Open Access 17-03-2023 | Original Article

Learning positioning policies for mobile manipulation operations with deep reinforcement learning

This work focuses on the operation of picking an object on a table with a mobile manipulator. We use deep reinforcement learning (DRL) to learn a positioning policy for the robot’s base by considering the reachability constraints of the arm. This …

Ander Iriondo, Elena Lazkano, Ander Ansuategi, Andoni Rivera, Iker Lluvia, Carlos Tubío

15-03-2023 | Original Article

Target-oriented multimodal sentiment classification by using topic model and gating mechanism

Multimodality sentiment classification of social media attracts increasing attention, whose main purpose is to predict the sentiment of the target mentioned in the posts. Current research mainly focuses on integrating the multimodal data, but …

Zhengxin Song, Yun Xue, Donghong Gu, Haolan Zhang, Weiping Ding

14-03-2023 | Original Article

A static video summarization approach via block-based self-motivated visual attention scoring mechanism

Since automatic visual semantic comprehension of video content is currently infeasible and unintelligent, key frames extracted from videos are inconsistent with human visual understanding. In this paper, a block-based self-motivated visual …

Wen-lin Li, Tong Zhang, Xiao Liu

Open Access 13-03-2023 | Original Article

CatSight, a direct path to proper multi-variate time series change detection: perceiving a concept drift through common spatial pattern

Detecting changes in data streams, with the data flowing continuously, is an important problem which Industry 4.0 has to deal with. In industrial monitoring, the data distribution may vary after a change in the machine’s operating point; this …

Arantzazu Flórez, Itsaso Rodríguez-Moreno, Arkaitz Artetxe, Igor García Olaizola, Basilio Sierra

11-03-2023 | Original Article

Online rule fusion model based on formal concept analysis

A rule is an effective representation of knowledge in formal concept analysis (FCA), which can express the relations between concepts. One of the main research directions of FCA is to develop rule-based classification algorithms. Rule-based …

Xiaohe Zhang, Degang Chen, Jusheng Mi

11-03-2023 | Original Article

An adaptive focused target feature fusion network for detection of foreign bodies in coal flow

In the process of conveying raw coal to the surface on conveyor belts, the raw coal is generally blended with foreign bodies, such as large pieces of gangue and damaged bolts, which can affect the quality of mined coal, damage the transportation …

Tao Ye, Zhikang Zheng, Yunwang Li, Xi Zhang, Xiangpeng Deng, Yu Ouyang, Zongyang Zhao, Xiaozhi Gao

Open Access 08-03-2023 | Original Article

TTL: transformer-based two-phase transfer learning for cross-lingual news event detection

Today, we have access to a vast data amount, especially on the internet. Online news agencies play a vital role in this data generation, but most of their data is unstructured, requiring an enormous effort to extract important information. Thus …

Hansi Hettiarachchi, Mariam Adedoyin-Olowe, Jagdev Bhogal, Mohamed Medhat Gaber

03-03-2023 | Original Article

Pathological image super-resolution using mix-attention generative adversarial network

Image super-resolution (SR) is a fundamental research task in low-level vision. Recently it has been applied to digital pathology to build transformations from low-resolution (LR) to super-resolved high-resolution (HR) images, which benefits …

Zhineng Chen, Jing Wang, Caiyan Jia, Xiongjun Ye

01-03-2023 | Original Article

A cross-validation framework to find a better state than the balanced one for oversampling in imbalanced classification

Imbalance classification has always been a popular research point in the application of machine learning, data mining and pattern recognition. At present, there are also many techniques to reduce the negative impact of imbalance on classification …

Qizhu Dai, Donggen Li, Shuyin Xia