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- SenticNet 6: Ensemble Application of Symbolic and Subsymbolic AI for Sentiment Analysis466
This work integrates logical reasoning within deep learning architectures to build a new version of SenticNet, a commonsense knowledge base for sentiment analysis, and applies it to the interesting problem of polarity detection from text.
- Word Embedding for Understanding Natural Language: A Survey241
This survey introduces the motivation and background of word embedding, the methods of text representation as preliminaries, as well as some existingword embedding approaches such as Neural Network Language Model and Sparse Coding Approach, along with their evaluation metrics.
- A Generative Model for category text generation167
Not only the proposed model is able to generate category sentences that enlarge the original dataset, but also it helps improve its generalization capability during supervised training, and is evaluated for the task of sentiment analysis.
- Learning multi-grained aspect target sequence for Chinese sentiment analysis164
This paper formalizes the problem of aspect-level sentiment analysis from a different perspective, i.e., that sentiment at aspect target level should be the main focus and proposes to explicitly model the aspect target and conduct sentiment classification directly at the aspect targets level via three granularities.
- Recent Developments in Recommender Systems: A Survey [Review Article]124
In this technical survey, the latest advancements in the field of recommender systems are comprehensively summarized, and the robustness, data bias, and fairness issues in recommender systems are analyzed.
- Disentangled Variational Auto-Encoder for semi-supervised learning97
A new model is proposed called Semi-supervised Disentangled VAE (SDVAE), which encodes the input data into disentangled representation and non-interpretable representation, then the category information is directly utilized to regularize the disentangling representation via the equality constraint.
- Learning binary codes with neural collaborative filtering for efficient recommendation systems80
A new deep learning framework is proposed for deep collaborative hashing codes on user–item ratings that adopts neural networks to better learn both user and item representations and make these close to binary codes such that the quantization loss is minimized.
- A survey on cybersecurity attacks and defenses for unmanned aerial systems73
A comprehensive review of UAS cybersecurity research, with a focus on attack and defense technologies, analyzes the UAS architecture and classifies security threats into four categories: communication network security, software security, payload security, and intelligent security.
- Multitask learning for emotion and personality traits detection63
This paper proposes a novel transferring based multitask learning framework that simultaneously predicts both personality traits and emotional behaviors and achieves the state-of-the-art performance across multiple famous personality and emotion datasets, even outperforming model-based models.
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- Phonetic-enriched text representation for Chinese sentiment analysis with reinforcement learning52
Experimental results on five different Chinese sentiment analysis datasets show that the inclusion of phonetic features significantly and consistently improves the performance of textual and visual representations and outshines the state-of-the-art Chinese character level representations.
- Hformer: highly efficient vision transformer for low-dose CT denoising50
Hformer, a novel supervised learning model for low-dose computer tomography (LDCT) denoising, combines the strengths of convolutional neural networks for local feature extraction and transformer models for global feature capture.
- Informal prototyping of continuous graphical interactions by demonstration50
Informal feedback showed that Monet is a promising approach to enabling more complete tool support for early stage UI design, by showing that Monet allows continuous interactions to be eas-ily integrated with event-based, discrete interactions.
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- PrimeNet: A Framework for Commonsense Knowledge Representation and Reasoning Based on Conceptual Primitives25
This work designs a new commonsense knowledge base, termed PrimeNet, organized in a three-layer structure: a small core of conceptual primitives, a bigger set of concepts that connect to such primitives, and an even larger layer of entities connecting to the concepts.
- Secure Software Engineering Education: Knowledge Area, Curriculum and Resources25
Current efforts and resources in secure software engineering education, including Common Body of Knowledge, reference curriculum, sample curriculum materials, hands-on exercises, and resources developed by industry and open source community are reviewed.
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- Data Augmentation and Classification of Sea–Land Clutter for Over-the-Horizon Radar Using AC-VAEGAN21
The experiment results show that the quality of samples synthesized by AC-VAEGAN is better than those synthesizing by the state-of-the-art GAN-based methods, and the data augmentation method is able to improve the classification performance in the case of the imbalanced and scarce sea–land clutter samples.
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- Graph routing between capsules20
A new capsule network with graph routing to learn both relationships, where capsules in each layer are treated as the nodes of a graph, and the approach combining bottom-up routing and top-down attention performs the best.
Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-12. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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