A5029722336- Topic Modeling
- Sentiment Analysis and Opinion Mining
- Text and Document Classification Technologies
- Advanced Text Analysis Techniques
- Image Enhancement Techniques
- Recommender Systems and Techniques
- Web Data Mining and Analysis
- Optical Systems and Laser Technology
- Infrared Target Detection Methodologies
- Advanced Graph Neural Networks
- Machine Learning in Healthcare
- Biomedical Text Mining and Ontologies
- Digital Marketing and Social Media
Hainan University
2024
Henan University
2020-2023
Recently, a lot of Chinese patients consult treatment plans through social networking platforms, but the medical text contains rich information, including large number nomenclatures and symptom descriptions. How to build an intelligence model automatically classify information consulted by recommend correct department for is very important. In order address problem insufficient feature extraction from low accuracy, this paper proposes dual channel classification model. The extracts at...
Tourism recommendation results are affected by many factors. Traditional methods have problems such as low accuracy and lack of personalization due to sparse data. This article uses implicit features contextual information, time-series travel trajectories, comment data address these issues. First, the Long Short-Term Memory (LSTM) network is introduced model basis, deals with input scenic spot tourist comments so on for feature extraction. Then, online behavior long-term interest preference...
The CNN-LSTM model has the advantages of combining Convolutional Neural Network (CNN) and Long-Short Term Memory (LSTM). It can perform timing analysis while extracting abstract features. is widely used in Computer Vision Natural Language Processing (NLP) fields achieved satisfactory results. However, for a large number samples complex text data, especially words with ambiguous meanings, word-level insufficient. Therefore, order to solve this issue, paper presents an improved Double Channel...
The number of tourist attractions reviews, travel notes and other texts has grown exponentially in the Internet age. Effectively mining users’ potential opinions emotions on attractions, helping to provide users with better recommendation services, which is great practical significance. This paper proposes a multi-channel neural network model called Pre-BiLSTM combined pre-training mechanism. uses combination coarse fine- granularity strategies extract features text information such as...