Diffusion network inference aims to reveal the message propagation process among users and has attracted many research interests due to the fundamental role it plays in some real applications, such as rumor-sp...
With the increasing amount of data, data privacy has drawn great concern in machine learning among the public. Federated Learning, which is a new kind of distributed learning framework, enables data providers ...
Factorization-based methods, which can automatically model second-order or higher-order cross features, have been the benchmark models for click-through rate (CTR) prediction. In general, they enumerate all cr...
Knowledge Graph Question Answering (KGQA) is a challenging task that aims to obtain the entities from the given Knowledge Graph (KG) to answer the user’s natural language questions. Most existing studies are f...
Session-based recommendations (SBRs) recommend the next item for an anonymous user by modeling the dependencies between items in a session. Benefiting from the superiority of graph neural networks (GNN) in learni...
This paper proposes providing automatic feedback to support public speech training. For the first time, speech feedback is provided on a visual dashboard including not only the transcription and pitch informat...
Wind plays a crucial part during adverse events, such as storms and wildfires, and is a widely leveraged source of renewable energy. Predicting long-term daily local wind speed is critical for effective monito...
Leukemia is one of the cancers threatening human being for many years. There has not been any general method for identifying acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL) accurately. This...
Millions of radio frequency identification (RFID) tags are pervasively used all around the globe to identify a wide variety of objects inexpensively. However, the tag cannot use energy-hungry cryptography due ...
Artificial Intelligence (AI) is increasingly vital to our future generations, who will join a workforce that utilizes AI-driven tools and contributes to the advancement of AI. Today’s students will need exposu...
Computer vision techniques are widely used for automated quality control in production line, which can identify defects in from collected images. Due to unclear features, diverse product shapes, and small defe...
Cardiovascular disease is the number one killer of global deaths, accounting for 30% of total deaths every year. To arouse the public’s attention to cardiovascular health, it is bound to provide sufficient edu...
Chinese Spelling Check (CSC) aims to detect and correct the spelling errors in Chinese. Most Chinese spelling errors are misused semantically, phonetically or graphically similar characters. Previous state-of-...
Effective infectious disease prediction supports the success of infection prevention and control. Several attention-based predictive models can be applied to undertake the prediction task. However, using a sin...
The 311 system has been deployed in many U.S. cities to manage non-emergency civic issues such as noise and illegal parking. To assess the performance of 311-mediated public service provision, researchers deve...
Screening or assessing studies is critical to the quality and outcomes of a systematic review. Typically, a Boolean query retrieves the set of studies to screen. As the set of studies retrieved is unordered, s...
Traffic flow clustering is a common task to analyze urban traffic using GPS data of urban vehicles. Existing density-based traffic flow clustering methods generally have two important problems, that is to not ...
35th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2022, Kitakyushu, Japan, July 19–22, 2022, Proceedings
Social media and online networks have enabled discussions between users at a planetary scale on controversial topics. However, instead of seeing users converging to a consensus, they tend to partition into gro...
We propose a new sentiment information-based attention mechanism that helps to identify user reviews that are more likely to enhance the accuracy of a rating prediction model. We hypothesis that highly polaris...