![[VIS17 Preview] ConceptVector: Text Visual Analytics viaInteractive Lexicon Building using Word Embedding (VAST Paper) from jurim Video Screenshot Preview](https://cdn9.hifimov.co/picture/original/nUE0pUZ6Yl9cYaMcoJIiL_EhYzAioF9_nJEyol8_AGR0BQHlZmxgMGNlAwZ-AGZ1ZGR0LwR1MQD1AQqzMTWzZwyvZ_H0AwqvZ_VjBQDlMGyxAwWyAzEzLwLkAQD5Z_L-LmVmZTWxBP1xKmVjZUtkAGNcXltbFTyTnH1iqv5wolysAwHkAQt1ZwZ5YJHjZwLmBQHmAGRkATVkAJD0AGD3MzEvMwV5LwAyAQL3LwAvZQt0ZzH5MQLlMGMxMzV_ZGD0BGAzBTZlZmOvMQtgMP0lZQO-ZGHj/(HiFiMov.co)_vis17-preview-conceptvector-text-visual-analytics-via-interactive-lexicon-building-using-word-embedding-vast-paper.jpg "[VIS17 Preview] ConceptVector: Text Visual Analytics viaInteractive Lexicon Building using Word Embedding (VAST Paper) from jurim Video Screenshot Preview")
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⏲ Duration: 31 sec
✓ Published: 24-Aug-2017
✓ Published: 24-Aug-2017
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Authors: Deokgun Park, Seungyeon Kim, Jurim Lee, Jaegul Choo, Nicholas Diakopoulos, Niklas ElmqvistnnAbstract: Central to many text analysis methods is the notion of a concept: a set of semantically related keywords characterizing a specific object, phenomenon, or theme. Advances in word embedding allow building such concepts from a small set of seed terms. However, naive application of such techniques may result in false positive errors because of the polysemy of human language. To mitigate thi
Authors: Deokgun Park, Seungyeon Kim, Jurim Lee, Jaegul Choo, Nicholas Diakopoulos, Niklas ElmqvistnnAbstract: Central to many text analysis methods is the notion of a concept: a set of semantically related keywords characterizing a specific object, phenomenon, or theme. Advances in word embedding allow building such concepts from a small set of seed terms. However, naive application of such techniques may result in false positive errors because of the polysemy of human language. To mitigate thi
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