Emotion computing using Word Mover's Distance features based on Ren_CECps.
In this paper, we propose an emotion separated method(SeTF·IDF) to assign the emotion labels of sentences with different values, which has a better visual effect compared with the values represented by TF·IDF in the visualization of a multi-label Chinese emotional corpus Ren_CECps. Inspired by the e...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2018-01-01
|
| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC5889067?pdf=render |
| _version_ | 1818272116592607232 |
|---|---|
| author | Fuji Ren Ning Liu |
| author_facet | Fuji Ren Ning Liu |
| author_sort | Fuji Ren |
| collection | DOAJ |
| description | In this paper, we propose an emotion separated method(SeTF·IDF) to assign the emotion labels of sentences with different values, which has a better visual effect compared with the values represented by TF·IDF in the visualization of a multi-label Chinese emotional corpus Ren_CECps. Inspired by the enormous improvement of the visualization map propelled by the changed distances among the sentences, we being the first group utilizes the Word Mover's Distance(WMD) algorithm as a way of feature representation in Chinese text emotion classification. Our experiments show that both in 80% for training, 20% for testing and 50% for training, 50% for testing experiments of Ren_CECps, WMD features get the best f1 scores and have a greater increase compared with the same dimension feature vectors obtained by dimension reduction TF·IDF method. Compared experiments in English corpus also show the efficiency of WMD features in the cross-language field. |
| first_indexed | 2024-12-12T21:36:57Z |
| format | Article |
| id | doaj.art-8c8ba4df821c42c9801ff3a06a826674 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-12T21:36:57Z |
| publishDate | 2018-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-8c8ba4df821c42c9801ff3a06a8266742022-12-22T00:11:10ZengPublic Library of Science (PLoS)PLoS ONE1932-62032018-01-01134e019413610.1371/journal.pone.0194136Emotion computing using Word Mover's Distance features based on Ren_CECps.Fuji RenNing LiuIn this paper, we propose an emotion separated method(SeTF·IDF) to assign the emotion labels of sentences with different values, which has a better visual effect compared with the values represented by TF·IDF in the visualization of a multi-label Chinese emotional corpus Ren_CECps. Inspired by the enormous improvement of the visualization map propelled by the changed distances among the sentences, we being the first group utilizes the Word Mover's Distance(WMD) algorithm as a way of feature representation in Chinese text emotion classification. Our experiments show that both in 80% for training, 20% for testing and 50% for training, 50% for testing experiments of Ren_CECps, WMD features get the best f1 scores and have a greater increase compared with the same dimension feature vectors obtained by dimension reduction TF·IDF method. Compared experiments in English corpus also show the efficiency of WMD features in the cross-language field.http://europepmc.org/articles/PMC5889067?pdf=render |
| spellingShingle | Fuji Ren Ning Liu Emotion computing using Word Mover's Distance features based on Ren_CECps. PLoS ONE |
| title | Emotion computing using Word Mover's Distance features based on Ren_CECps. |
| title_full | Emotion computing using Word Mover's Distance features based on Ren_CECps. |
| title_fullStr | Emotion computing using Word Mover's Distance features based on Ren_CECps. |
| title_full_unstemmed | Emotion computing using Word Mover's Distance features based on Ren_CECps. |
| title_short | Emotion computing using Word Mover's Distance features based on Ren_CECps. |
| title_sort | emotion computing using word mover s distance features based on ren cecps |
| url | http://europepmc.org/articles/PMC5889067?pdf=render |
| work_keys_str_mv | AT fujiren emotioncomputingusingwordmoversdistancefeaturesbasedonrencecps AT ningliu emotioncomputingusingwordmoversdistancefeaturesbasedonrencecps |