An increasing number of people suffering from mental health conditions resort to online resources (specialized websites, social media, etc.) share their feelings. Early depression detection using media data through deep learning models can help change life trajectories and save lives. But the accuracy these was not satisfying due real-world imbalanced distributions. To tackle this problem, we propose a model (X-A-BiLSTM) for in data. The X-A-BiLSTM consists two essential components: first...

More users suffering from depression turn to online forums express their problems and seek help. In such forums, there is often a large volume of posts with sensitive content, indicating that the user has risk suicide self-harm. Early detection using appropriate deep learning models social media data can prevent potential However, existing are not powerful enough capture critical sentiment information published by each user, which makes performance these satisfying. To address this problem,...

The widespread use of social media provides a large amount data for public sentiment analysis. Based on data, researchers can study opinions human papillomavirus (HPV) vaccines using machine learning-based approaches that will help us understand the reasons behind low vaccine coverage. However, is usually unannotated, and annotation costly. lack an abundant annotated dataset limits application deep learning methods in effectively training models. To tackle this problem, we propose three...

Abstract Event Detection (ED) is a crucial information extraction task that aims to identify the event triggers and classify them into predefined types. However, most existing methods did not perform well when processing events with implicit triggers. And considered ED as sentence-level task, lacking effective context for semantics. Moreover, how maintain good performance under low resource conditions still needs further study. To address these problems, we propose novel end-to-end model...

Biomedical knowledge graphs (BMKGs), which may facilitate precision medicine and clinical decision support, have become more important in healthcare practice research. A lot of challenges still remain their construction curation due to the complex high demanding nature task. Most current BMKGs are manually compiled, is particularly time-consuming labor-intensive. Some automatically generated but rely heavily on quality source data. Furthermore, most them not fully integrate or represent...

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Locality Preserving Projection is a method which can extract the feature and reduce dimensionality effectively, has been widely used in face recognition. However, it also an unsupervised method, image vector-based needing to covert into vector. This conversion not only breaks local structural information, but brings lots of problems, such as dimension these converted vectors too high encounters small sample size problem. And no directly relation classification. In order improve performance...

Aspect-based sentiment analysis (ABSA) aims to determine the polarity of specific aspect for a given sentence. Attention-based models are widely used in this task because they can extract semantic information between context words make up deficiency sequence encoding. In order enhance extraction high-quality information, we propose novel joint model with Second-Order Features and Matching Attention (SOMA) aspect-based analysis. Firstly, introduce second-order statistics vital interact...

according to the current key management scheme exist large computation, trusted centre and update cycle size is difficult determine problems, we proposed a that based on ECC fully self-organization Ad hoc in this paper. The use instead of RSA for computation; order solve centre, self-organization; by using double overcome regular updating problem. Computational cost program has small computation safe, reliability good scalability large-scale network.

<sec> <title>BACKGROUND</title> The process of developing new drugs is very tortuous. Bringing to the market requires billions dollars in investment, which takes an average about 13-15 years. In order overcome these difficulties, more and companies pharmaceutical have begun adopt strategy “repositioning drugs” instead drug development. </sec> <title>OBJECTIVE</title> Traditional repositioning methods often focus on relationships between entities, ignoring semantic component relationships....