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Cognitive difference text classification in online knowledge collaboration based on SA-BiLSTM hybrid model. [PDF]
Sci RepLiu F, Zhao N, Zhu G.
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Comparative analysis of BERT and FastText representations on crowdfunding campaign success prediction. [PDF]
PeerJ Comput SciGunduz H.
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Leveraging word embeddings to enhance co-occurrence networks: A statistical analysis. [PDF]
PLoS OneAmancio DR, Machicao J, Quispe LVC.
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MLR-predictor: a versatile and efficient computational framework for multi-label requirements classification. [PDF]
Front Artif IntellSaleem S +4 more
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Text Classification Model Based on fastText
2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS), 2020Most text classification models based on traditional machine learning algorithms have problems such as curse of dimensionality and poor performance. In order to solve the above problems, this paper proposes a text classification model based on fastText.
Tengjun Yao, Zhengang Zhai, Bingtao Gao
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A Deep Investigation into fastText
2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS), 2019The researches on text classification range from traditional machine learning methods which depend on handcrafted features to recent deep learning models which learn complex and non-linear relationships automatically. While neural models have been proven to be effective for text classification, they operate like a black box and offer no ...
Jincheng Xu, Qingfeng Du
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Detection and classification of malware based on FastText
2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS), 2020Nowadays, the Internet has penetrated into every corner of people's lives. It brings convenience to my life as well as certain risks. Millions of new types of malware appear every day, affecting thousands or even millions of home computer users. And attackers can use fully automated design and reuse malware, which makes the threshold for cybercrime ...
Luming Feng, Yanpeng Cui, Jianwei Hu
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Enhancing Short Text Topic Modeling with FastText Embeddings
2020 International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE), 2020Over the past few years, we have experienced the rapid development of online social media, which produced a variety of short texts. It is important to understand the topic patterns of these short texts. Because of data sparsity, traditional topic models are not suitable for short text topic analysis.
Fan Zhang, Wang Gao, Yuan Fang, Bo Zhang
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Improving FastText with inverse document frequency of subwords
Pattern Recognition Letters, 2020Abstract Word embedding is important in natural language processing, and word2vec is known as a representative algorithm. However, word2vec and many other dictionary-based word embedding algorithms create word vectors only for words that appear in the training data, ignoring morphological features of these words. The FastText algorithm was previously
Jaekeol Choi, Sang-Woong Lee
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Malware Detection and Classification Using fastText and BERT
2021 9th International Symposium on Digital Forensics and Security (ISDFS), 2021Among the types of cyber-attacks, malware that causes high financial losses for institutions and individuals is the biggest threat to computer systems. Kinds of malware increase day-by-day and new types are released, which can easily infect our computers through injection vectors such as e-mail, websites, web applications that we use constantly.
Salih Yesir, Ibrahim Sogukpinar
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