A5032685155- Advanced Image and Video Retrieval Techniques
- Online Learning and Analytics
- Image Retrieval and Classification Techniques
- Video Analysis and Summarization
- Intelligent Tutoring Systems and Adaptive Learning
- Educational Technology and Assessment
- Machine Learning and Data Classification
- Human Pose and Action Recognition
- Learning Styles and Cognitive Differences
- Neural Networks and Applications
- Face and Expression Recognition
- Advanced Graph Neural Networks
- Multimodal Machine Learning Applications
- Advanced Clustering Algorithms Research
- Recommender Systems and Techniques
Huawei Technologies (China)
2022-2023
Huawei Technologies (France)
2023
Google (United States)
2010
Zhejiang University
2008-2009
Zhejiang University of Science and Technology
2008
Videos such as movies or TV episodes usually need to divide the long storyline into cohesive units, i.e., scenes, facilitate understanding of video semantics. The key challenge lies in finding boundaries scenes by comprehensively considering complex temporal structure and semantic information. To this end, we introduce a novel Context-Aware Transformer (CAT) with self-supervised learning framework learn high-quality shot representations, for generating well-bounded scenes. More specifically,...
Computerized Adaptive Testing (CAT) refers to an online system that adaptively selects the best-suited question for students with various abilities based on their historical response records. Compared traditional CAT methods heuristic rules, recent data-driven obtain higher performance by learning from large-scale datasets. However, most only focus quality objective of predicting student ability accurately, but neglect concept diversity or exposure control, which are important considerations...
Online education, which educates students that cannot be present at school, has become an important supplement to traditional education. Without the direct supervision and instruction of teachers, online education is always concerned with potential distractions misunderstandings. Learning Style Classification (LSC) proposed analyze learning behavior patterns users, based on personalized paths are generated help them learn maintain their interests.
With the development of online education system, personalized recommendation has played an essential role. In this paper, we focus on developing path systems that aim to generating and recommending entire learning given user in each session. Noticing existing approaches fail consider correlations concepts path, propose a novel framework named Set-to-Sequence Ranking-based Concept-aware Learning Path Recommendation (SRC), which formulates task under set-to-sequence paradigm. Specifically,...
Does adding more training data always help improve the effectiveness of a machine-learning or pattern-recognition task? Recent evidences in machine translation and speech recognition seem to suggest that data-driven approach outperforms traditional model-based approach. Instead carefully modeling rules their exceptions, relies on identifying similar patterns massive datasets then uses predict labels (or other outcomes) unseen instances. In this work, we compare representative schemes an...
Computerized Adaptive Testing(CAT) refers to an online system that adaptively selects the best-suited question for students with various abilities based on their historical response records. Most CAT methods only focus quality objective of predicting student ability accurately, but neglect concept diversity or exposure control, which are important considerations in ensuring performance and validity CAT. Besides, students' records contain valuable relational information between questions...