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- Visual-Textual Joint Relevance Learning for Tag-Based Social Image Search465
An approach that simultaneously utilizes both visual and textual information to estimate the relevance of user tagged images is proposed, and the relevance estimation is determined with a hypergraph learning approach.
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- N Doping to ZnO Nanorods for Photoelectrochemical Water Splitting under Visible Light: Engineered Impurity Distribution and Terraced Band Structure259
N gradient-doped ZnO NRAs can not only utilize the visible light irradiation but also efficiently drive photo-induced electron and hole transfer via the terraced band structure and provide novel insights into doped photoelectrode materials for solar water splitting.
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- SMR: Medical Knowledge Graph Embedding for Safe Medicine Recommendation224
Safe Medicine Recommendation (SMR) is the first to learn embeddings of a patient-disease-medicine graph for medicine recommendation in the world and jointly embeds diseases, medicines, patients, and their corresponding relations into a shared lower dimensional space.
- Maximum Correntropy Unscented Kalman Filter for Spacecraft Relative State Estimation111
A new algorithm called maximum correntropy unscented Kalman filter (MCUKF) is proposed and applied to relative state estimation in space communication networks and can enhance the robustness of UKF against impulsive noises.
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- A query expansion method for retrieving online BIM resources based on Industry Foundation Classes100
This work develops a prototype semantic search engine, named BIMSeek, for retrieving online BIM resources, and presents an automatic query expansion method, which outperforms traditional keyword-based methods and WordNet-based query expansion methods.
- Efficiently embedding dynamic knowledge graphs93
This paper proposes a new context-aware Dynamic Knowledge Graph Embedding method, DKGE, which supports the embedding learning in an online fashion and can also learn KG embedding from scratch.
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- Safe Medicine Recommendation via Medical Knowledge Graph Embedding73
Safe Medicine Recommendation (SMR) is the first to learn embeddings of a patient-disease-medicine graph for medicine recommendation in the world and jointly embeds diseases, medicines, patients, and their corresponding relations into a shared lower dimensional space.
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- A Survey of Techniques for Constructing Chinese Knowledge Graphs and Their Applications67
This paper aims to introduce the techniques of constructing Chinese knowledge graphs and their applications, as well as analyse the impact of knowledge graph on OBOR.
- CdS/CdSe Core–Shell Nanorod Arrays: Energy Level Alignment and Enhanced Photoelectrochemical Performance63
CdS/CdSe core-shell arrays gave a maximum photocurrent of 5.3 mA/cm(2), which was 4 and 11 times as large as bare CdS and CdSe, respectively.
- EgoTextVQA: Towards Egocentric Scene-Text Aware Video Question Answering61
This work introduces EgoTextVQA, a novel and rigorously constructed benchmark for egocentric QA assistance involving scene text, and comprehensively evaluates 10 prominent multimodal large language models.
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- Towards Empty Answers in SPARQL: Approximating Querying with RDF Embedding48
An RDF graph embedding based framework to solve the SPARQL empty-answer problem in terms of a continuous vector space and can significantly improve the quality of approximate answers and speed up the generation of alternative queries.
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- Fair Representation Learning for Recommendation: A Mutual Information Perspective43
This paper re-define recommendation fairness with a novel two-fold mutual information objective, and proposes novel mutual information (upper/lower) bounds with contrastive information estimation for model optimization.
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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 2026-10-15. 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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