Honghao Li
Biographic Data
| ID | 4416613 |
|---|---|
| NAME | Honghao Li |
| GIVEN NAMES | Honghao |
| FAMILY NAME | Li |
| SIGNATURE | LI H |
| AFFILIATIONS | China University of Mining and Technology |
| ORCID | 0000-0002-8854-9879 |
| VERIFIED | Yes |
| TOTAL WORKS | 8 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 8 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Tf4ctr
Effective feature interaction modeling is critical for enhancing the accuracy of click-through rate (CTR) prediction in industrial recommender systems. Most of the current deep CTR models resort to building complex network architectures to better capture intricate feature interactions (FIs) or user behaviors. However, we identify two limitations in these models: 1) the samples given to the model are undifferentiated, which may lead the model to l…
Optimizing Feature Interaction via Information Bottleneck for CTR Prediction
Click-through rate (CTR) prediction plays a pivotal role in recommender systems and online advertising by estimating the probability of user engagement with recommended items or advertisements. However, existing methodologies encounter multiple challenges. First, current approaches often struggle to maintain robustness in the presence of noise. This challenge arises from the inherent complexity of real-world data, where noisy or irrelevant featur…
Dual-Domain Collaborative Denoising for Social Recommendation
Social recommendation leverages social network to complement user–item interaction data for recommendation task, aiming to mitigate the data sparsity issue in recommender systems. The information propagation mechanism of graph neural networks (GNNs) aligns well with the process of social influence diffusion in social network, thereby can theoretically boost the performance of recommendation. However, existing social recommendation methods encount…
The impact of audio–visual landscape perception in tourism-oriented traditional Yao villages on the tourism experience
In recent years, many well-preserved traditional ethnic minority villages in China, designated as cultural heritage sites, have gradually become tourist destinations. Improving the tourism experience in these villages has become a key task. The audio–visual landscape plays the most important role in evaluating key indicators of the tourism experience, including tourism satisfaction, perceived restoration, and place attachment. This study focuses …
How does public perception influence resistance in Nimby conflicts? — A qualitative comparative analysis of 25 cases in China
Multi-task deep learning strategy for map-type classification
MapSR
The purpose of multisource map super-resolution is to reconstruct high-resolution maps based on low-resolution maps, which is valuable for content-based map tasks such as map recognition and classification. However, there is no specific super-resolution method for maps, and the existing image super-resolution methods often suffer from missing details when reconstructing maps. We propose a map super-resolution (mapSR) model that fuses local and gl…
Model and Data Integrated Transfer Learning for Unstructured Map Text Detection
The emergence of the third information wave makes extensive maps available to be generated by volunteered ways, never specially designed and generated by professional institutes alone. These large-scale images-based volunteered maps created by the public provide plentiful geographical information regarding a place while posing a challenge for recognizing the unstructured text in these maps for previous approaches to standard map text detection. M…
No prominent works on this page.
MapSR
The purpose of multisource map super-resolution is to reconstruct high-resolution maps based on low-resolution maps, which is valuable for content-based map tasks such as map recognition and classification. However, there is no specific super-resolution method for maps, and the existing image super-resolution methods often suffer from missing details when reconstructing maps. We propose a map super-resolution (mapSR) model that fuses local and gl…
Model and Data Integrated Transfer Learning for Unstructured Map Text Detection
The emergence of the third information wave makes extensive maps available to be generated by volunteered ways, never specially designed and generated by professional institutes alone. These large-scale images-based volunteered maps created by the public provide plentiful geographical information regarding a place while posing a challenge for recognizing the unstructured text in these maps for previous approaches to standard map text detection. M…
Multi-task deep learning strategy for map-type classification
Dual-Domain Collaborative Denoising for Social Recommendation
Social recommendation leverages social network to complement user–item interaction data for recommendation task, aiming to mitigate the data sparsity issue in recommender systems. The information propagation mechanism of graph neural networks (GNNs) aligns well with the process of social influence diffusion in social network, thereby can theoretically boost the performance of recommendation. However, existing social recommendation methods encount…
The impact of audio–visual landscape perception in tourism-oriented traditional Yao villages on the tourism experience
In recent years, many well-preserved traditional ethnic minority villages in China, designated as cultural heritage sites, have gradually become tourist destinations. Improving the tourism experience in these villages has become a key task. The audio–visual landscape plays the most important role in evaluating key indicators of the tourism experience, including tourism satisfaction, perceived restoration, and place attachment. This study focuses …
How does public perception influence resistance in Nimby conflicts? — A qualitative comparative analysis of 25 cases in China
Tf4ctr
Effective feature interaction modeling is critical for enhancing the accuracy of click-through rate (CTR) prediction in industrial recommender systems. Most of the current deep CTR models resort to building complex network architectures to better capture intricate feature interactions (FIs) or user behaviors. However, we identify two limitations in these models: 1) the samples given to the model are undifferentiated, which may lead the model to l…
Optimizing Feature Interaction via Information Bottleneck for CTR Prediction
Click-through rate (CTR) prediction plays a pivotal role in recommender systems and online advertising by estimating the probability of user engagement with recommended items or advertisements. However, existing methodologies encounter multiple challenges. First, current approaches often struggle to maintain robustness in the presence of noise. This challenge arises from the inherent complexity of real-world data, where noisy or irrelevant featur…
Computer Science (6 works) · Artificial Intelligence (4 works) · Deep learning (3 works) · Geography (3 works) · Advanced Image and Video Retrieval Techniques (2 works) · Cartography (2 works) · Engineering (2 works) · Generalization (2 works) · Mathematics (2 works) · Perception (2 works)