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Along with the rapid technological and commercial innovation on e-commerce platforms, an increasing number of frauds cause great harm to these platforms. Many frauds are conducted by organized groups of fraudsters for higher efficiency and lower costs, ...

The primary method for news recommendations revolves around leveraging the user’s browsing history to gauge their interests. Existing models prioritize analyzing news content to infer user interests, ignoring the role of label category information ...

This paper introduces RealityEffects, a desktop authoring interface designed for editing and augmenting 3D volumetric videos with object-centric annotations and visual effects. RealityEffects enhances volumetric capture by introducing a novel method for ...

Event Causality Extraction (ECE) aims to extract the cause-effect event pairs with their structured event information from plain texts. As far as we know, the existing ECE methods mainly focus on the correlation between arguments, without explicitly ...

Graph Convolutional Networks (GCNs) has shown promise in recommendation systems. However, a critical issue known as the over-smoothing problem has been identified in GCN models. This problem arises as the number of layers in the model increases, ...

ChatGPT has received considerable attention in education, particularly in programming education because of its capabilities in automated code generation and program repairing and scoring. However, few empirical studies have investigated the use of ChatGPT ...

Along with the rapid technological and commercial innovation on the e-commerce platforms, there are an increasing number of frauds that bring great harm to these platforms. Many frauds are conducted by organized groups of fraudsters for higher efficiency ...

Argument unit recognition and classification (AURC) is a promising and critical research topic in argument mining, which aims to extract the argument units that express support or opposing stance in a given argumentative text under ...

We present RealityTalk, a system that augments real-time live presentations with speech-driven interactive virtual elements. Augmented presentations leverage embedded visuals and animation for engaging and expressive storytelling. However, existing ...

Stance detection can help gain different perspectives into important events, e.g., whether people are in favor of or against certain claim. Most previous work use sentiment information to assist in stance detection. However, they do ...

Compared with explicit sentiment analysis that attracts considerable attention, implicit sentiment analysis is a more difficult task due to the lack of sentimental words. The abundant information in an external sentimental knowledge ...

• A sentimental commonsense knowledge graph embedded multi-polarity orthogonal attention model is proposed to learn the implication of the implicit sentiment. ...

Existing studies on emotion analysis in conversations have mainly focused on recognizing the emotion of a given utterance. This paper investigates the task of emotion inference in conversations, which explores how the utterances affect ...

Existing link prediction methods focus on mining relations of nodes in terms of network structure, ignoring rich attributes of nodes. In the micro-blog social networks, text contents describe users’ diverse behaviors, which depicts ...

• A social relation extraction method is proposed via semantic association of texts.

In heterogeneous e-commerce recommender systems, the type and attribute information of users and products contain rich semantics, which can benefit the prediction and explanation of user ratings of interesting items. Existing studies ...

• A novel heterogeneous type-specific entity representation method is proposed.
• A ...

Live-streaming platforms have recently gained significant popularity by attracting an increasing number of young users and have become a very promising form of online shopping. Similar to the traditional online shopping platforms such as Taobao, live-...

Memory bandwidth utilization has become the key performance bottleneck for state-of-the-art variants of neural network kernels. Current structures such as depth-wise, point-wise and atrous convolutions have already introduced diverse and discontinuous ...

Sentiment analysis has been a popular field in natural language processing. Sentiments can be expressed explicitly or implicitly. Most current studies on sentiment analysis focus on the identification of explicit sentiments. However, ...

Recent years have witnessed the widespread success of convolutional neural networks (CNNs) in computer vision and multimedia. The CNNs based background subtraction methods, which are effective for addressing the challenges (such as shadows, ...

The rapid development of technology makes learning goals much more complex, diverse, and keeping changing. In reality, each product of design must be 'ultimately particular', which complicates the holistic learning objectives of a technology training ...

Along with the development of computer technology and the enlargement of simulation application, various simulation systems that based on different architectures are emerging. Bridging heterogeneous simulation systems via gateway to build large-scare ...