210 citations · 584 across the 37 of their papers we have counts for
11 papers · 1 filter
DeepVS: An Efficient and Generic Approach for Source Code Modeling Usage
Yasir Hussain, Zhiqiu Huang, Yu Zhou +1
The source code suggestions provided by current IDEs are mostly dependent on static type learning. These suggestions often end up proposing irrelevant suggestions for a peculiar co…
Deep Transfer Learning for Source Code Modeling
Yasir Hussain, Zhiqiu Huang, Yu Zhou +1
In recent years, deep learning models have shown great potential in source code modeling and analysis. Generally, deep learning-based approaches are problem-specific and data-hungr…
Deep Collaborative Filtering with Multi-Aspect Information in Heterogeneous Networks
Chuan Shi, Xiaotian Han, Li Song +4
Recently, recommender systems play a pivotal role in alleviating the problem of information overload. Latent factor models have been widely used for recommendation. Most existing l…
Behavior-aware Service Access Control Mechanism using Security Policy Monitoring for SOA Systems
Yunfei Meng, Zhiqiu Huang, Senzhang Wang +3
Service-oriented architecture (SOA) system has been widely utilized at many present business areas. However, SOA system is loosely coupled with multiple services and lacks the rele…
Label-Aware Graph Convolutional Networks
Hao Chen, Yue Xu, Feiran Huang +5
Recent advances in Graph Convolutional Networks (GCNs) have led to state-of-the-art performance on various graph-related tasks. However, most existing GCN models do not explicitly…
Deep Learning for Spatio-Temporal Data Mining: A Survey
Senzhang Wang, Jiannong Cao, Philip S. Yu
With the fast development of various positioning techniques such as Global Position System (GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly av…
Hierarchical Taxonomy-Aware and Attentional Graph Capsule RCNNs for Large-Scale Multi-Label Text Classification
Hao Peng, Jianxin Li, Qiran Gong +5
CNNs, RNNs, GCNs, and CapsNets have shown significant insights in representation learning and are widely used in various text mining tasks such as large-scale multi-label text clas…
Dynamic Network Embedding via Incremental Skip-gram with Negative Sampling
Hao Peng, Jianxin Li, Hao Yan +5
Network representation learning, as an approach to learn low dimensional representations of vertices, has attracted considerable research attention recently. It has been proven ext…
Mutual Clustering on Comparative Texts via Heterogeneous Information Networks
Jianping Cao, Senzhang Wang, Danyan Wen +3
Currently, many intelligence systems contain the texts from multi-sources, e.g., bulletin board system (BBS) posts, tweets and news. These texts can be ``comparative'' since they m…
Multi-Hot Compact Network Embedding
Chaozhuo Li, Senzhang Wang, Philip S. Yu +1
Network embedding, as a promising way of the network representation learning, is capable of supporting various subsequent network mining and analysis tasks, and has attracted growi…
CodeGRU: Context-aware Deep Learning with Gated Recurrent Unit for Source Code Modeling
Yasir Hussain, Zhiqiu Huang, Yu Zhou +1
Recently deep learning based Natural Language Processing (NLP) models have shown great potential in the modeling of source code. However, a major limitation of these approaches is…