Multi-task learning for toxic comment classification and rationale extraction [0.03%]
用于毒舌评论分类和原因提取的多任务学习方法
Kiran Babu Nelatoori,Hima Bindu Kommanti
Kiran Babu Nelatoori
Social media content moderation is the standard practice as on today to promote healthy discussion forums. Toxic span prediction is helpful for explaining the toxic comment classification labels, thus is an important step towards building a...
Germán Braun,Pablo Rubén Fillottrani,C Maria Keet
Germán Braun
Complex system development and maintenance face the challenge of dealing with different types of models due to language affordances, preferences, sizes, and so forth that involve interaction between users with different levels of proficienc...
SentiCode: A new paradigm for one-time training and global prediction in multilingual sentiment analysis [0.03%]
基于多语言迁移学习的一次训练跨域预测情感分析模型
Mohamed Raouf Kanfoud,Abdelkrim Bouramoul
Mohamed Raouf Kanfoud
The main objective of multilingual sentiment analysis is to analyze reviews regardless of the original language in which they are written. Switching from one language to another is very common on social media platforms. Analyzing these mult...
How to deal with negative preferences in recommender systems: a theoretical framework [0.03%]
推荐系统中处理负向偏好的理论框架
Federica Cena,Luca Console,Fabiana Vernero
Federica Cena
Negative information plays an important role in the way we express our preferences and desires. However, it has not received the same attention as positive feedback in recommender systems. Here we show how negative user preferences can be e...
Attention-based hybrid CNN-LSTM and spectral data augmentation for COVID-19 diagnosis from cough sound [0.03%]
基于注意力的混合CNN-LSTM和光谱数据增强的咳嗽声音新型冠状病毒肺炎诊断方法
Skander Hamdi,Mourad Oussalah,Abdelouahab Moussaoui et al.
Skander Hamdi et al.
COVID-19 pandemic has fueled the interest in artificial intelligence tools for quick diagnosis to limit virus spreading. Over 60% of people who are infected complain of a dry cough. Cough and other respiratory sounds were used to build diag...
A sampling approach to Debiasing the offline evaluation of recommender systems [0.03%]
用于推荐系统脱偏离线评估的抽样方法研究
Diego Carraro,Derek Bridge
Diego Carraro
Offline evaluation of recommender systems (RSs) mostly relies on historical data, which is often biased. The bias is a result of many confounders that affect the data collection process. In such biased data, user-item interactions are Missi...
Areeba Umair,Elio Masciari
Areeba Umair
The world has to face health concerns due to huge spread of COVID. For this reason, the development of vaccine is the need of hour. The higher vaccine distribution, the higher the immunity against coronavirus. Therefore, there is a need to ...
Antonio Galli,Elio Masciari,Vincenzo Moscato et al.
Antonio Galli et al.
Nowadays, really huge volumes of fake news are continuously posted by malicious users with fraudulent goals thus leading to very negative social effects on individuals and society and causing continuous threats to democracy, justice, and pu...
A spiral-like method to place in the space (and interact with) too many values [0.03%]
一种螺旋形的方法来在空间中放置（并交互）太多的价值
Yannis Tzitzikas,Maria-Evangelia Papadaki,Manos Chatzakis
Yannis Tzitzikas
Modern information systems have to support the user in managing, understanding and interacting with, more and more data. Visualization could help users comprehend information more easily and reach conclusions in relative shorter time. Howev...
Analysis of information cascading and propagation barriers across distinctive news events [0.03%]
基于不同新闻事件的信息级联与传播屏障分析
Abdul Sittar,Dunja Mladenić,Marko Grobelnik
Abdul Sittar
News reporting, on events that occur in our society, can have different styles and structures, as well as different dynamics of news spreading over time. News publishers have the potential to spread their news and reach out to a large numbe...