Skip-Gram-KR: Korean Word Embedding for Semantic Clustering
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2905252
Abstract: Deep learning algorithms are used in various applications for pattern recognition, natural language processing, speech recognition, and so on. Recently, neural network-based natural language processing techniques use fixed length word embedding. Word embedding is a… read more here.
Keywords: skip gram; word; korean word; gram korean ... See more keywords
Cross-Network Skip-Gram Embedding for Joint Network Alignment and Link Prediction
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2020.2997861
Abstract: Link prediction and network alignment are two fundamental and interleaved tasks in network analysis. In this paper, we propose a novel cross-network embedding model under the Skip-gram framework, which alternately performs link prediction and network… read more here.
Keywords: network alignment; link prediction; network; link ... See more keywords
Word2vec convolutional neural networks for classification of news articles and tweets
Sign Up to like & getrecommendations! Published in 2019 at "PLoS ONE"
DOI: 10.1371/journal.pone.0220976
Abstract: Big web data from sources including online news and Twitter are good resources for investigating deep learning. However, collected news articles and tweets almost certainly contain data unnecessary for learning, and this disturbs accurate learning.… read more here.
Keywords: news; articles tweets; skip gram; model ... See more keywords