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Chapter and Conference Paper
Text Causal Discovery Based on Sequence Structure Information
Causality forms the basis for reasoning and decision-making in artificial intelligence systems. To take advantage of the vast amount of textual data available today, causal discovery from text has become a sig...
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Chapter and Conference Paper
Multimodal Causal Relations Enhanced CLIP for Image-to-Text Retrieval
Traditional image-to-text retrieval models learn joint representations by aligning multimodal features, typically learning the weak correlation between image and text data which can introduce noise during moda...
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Chapter and Conference Paper
A Fine-Grained Image Description Generation Method Based on Joint Objectives
The goal of fine-grained image description generation techniques is to learn detailed information from images and simulate human-like descriptions that provide coherent and comprehensive textual details about ...
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Chapter and Conference Paper
Video Rumor Classification Based on Multi-modal Theme and Keyframe Fusion
In recent years, short video platforms have become the main source of online rumors. According to the statistics of Shanghai online rumor refutation platform in 2021, the number of short video rumors was about...
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Chapter and Conference Paper
Attention and Multi-granied Feature Learning for Baggage Re-identification
The current baggage re-identification methods only consider the global coarse-grained features while ignoring the fine-grained features. To deal with this issue, we proposed a simple and efficient multi-granul...
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Chapter and Conference Paper
Syntactic Dependency Constraint Based Graph Convolutional Network for Aspect Level Sentiment Classification
Aspect-Level Sentiment Classification (ALSC) aims to predict sentiment polarities of different aspects within sentences or documents. In the previous works, due to the problem of long-range gradient vanishing bet...
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Chapter and Conference Paper
Sentiment Analysis of Chinese Complex Long Sentences Based on Reinforcement Learning
Sentiment Analysis is a hot topic of Natural Language Processing (NLP). There have been relatively good solutions to general sentiment analysis problems, but in the face of the complex long sentences and the c...
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Chapter and Conference Paper
An Improved SSD-Based Gastric Cancer Detection Method
Gastric cancer is one of the malignant cancers with a very high fatal rate, and early detection plays an essential role in the treatment and improves the five-year 5-year survival rate. In this study, we an im...
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Chapter and Conference Paper
A Semi-supervised Video Object Segmentation Method Based on Adaptive Memory Module
Video object segmentation has becoming a hot research topic in the computer vision society, with a wide range of applications, such as autonomous driving, video editing, and video surveillance. However, due to...
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Chapter and Conference Paper
Law Article Prediction via a Codex Enhanced Multi-task Learning Framework
Automatic law article prediction aims to determine appropriate laws for a case by analyzing its corresponding fact description. This research constitutes a relatively new area which has emerged from recommende...
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Chapter and Conference Paper
Text Generation from Triple via Generative Adversarial Nets
Text generation plays an influential role in NLP (Natural Language Processing), but this task is still challenging. In this paper, we focus on generating text from a triple (entity, relation, entity), and we p...
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Article
Chinese microblog users’ sentiment-based traffic condition analysis
With the increasing number of vehicles in China, traffic condition analysis is of great significance to urban planning and public administration. However, the state-of-the-art traffic condition analysis approa...
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Article
Fuzzy cerebellar model articulation controller network optimization via self-adaptive global best harmony search algorithm
Fuzzy cerebellar model articulation controller (FCMAC) networks with excellent nonlinear appropriation ability and simple implementation are used to solve complex uncertainties problems in engineering applicat...
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Chapter and Conference Paper
Traffic Condition Analysis Based on Users Emotion Tendency of Microblog
Analysis of traffic condition is of great significance to urban planning and public administration. However, traditional traffic condition analysis approaches mainly rely on sensors, which are high-cost and li...
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Chapter and Conference Paper
Sentiment Analysis Model Based on Structure Attention Mechanism
Since the long short-term memory (LSTM) network is a sequential structure, it is difficult to effectively represent the structural level information of the context. Sentiment analysis based on the original LST...
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Chapter and Conference Paper
Content Representation for Microblog Rumor Detection
In recent years, various social network applications have emerged to meet users demand of social activity. As the biggest Chinese Microblog platform, Sina Weibo not only provides users with a lot of informatio...
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Chapter and Conference Paper
SentiNet: Mining Visual Sentiment from Scratch
An image is worth a thousand of words for sentiment expression, but the semantic gap between low-level pixels and high-level sentiment make visual sentiment analysis difficult. Our work focuses on two aspects ...
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Article
Visual sentiment topic model based microblog image sentiment analysis
With a growing number of images being used to express opinions in Microblog, text based sentiment analysis is not enough to understand the sentiments of users. To obtain the sentiments implied in Microblog ima...
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Article
A cross-media public sentiment analysis system for microblog
Since classical public sentiment analysis systems for microblog are based on the text sentiment analysis, it is difficult to determine the sentiment of short text without clear sentiment words in microblog pos...
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Chapter and Conference Paper
Blog Topic Diffusion Prediction Model Based on Link Information Flow
How to predict the topic diffusion is a challenging research work in social media data mining. The classical research works in Twitter and Micorblog mainly focus on diffusion links that ignore the importance o...
