Papers by Hiroki Okamoto
Mining Tweets that refer to TV programs with Deep Neural Networks (D19-55)
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| Challenge: | opinion mining is a popular natural language processing technique, but a problem is robustness for user-generated texts . a recent study shows that a model that handles context can extract the opinion target with 90% accuracy . |
| Approach: | They propose a model that handles context in many natural language processing areas to solve a problem of extracting opinion references from text. |
| Outcome: | Experiments on tweets that refer to television programs show the proposed model can extract opinion references with more than 90% accuracy. |
Label Embedding using Hierarchical Structure of Labels for Twitter Classification (D19-1)
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| Challenge: | Twitter is used for disaster monitoring and news material gathering . we propose a method that can consider the hierarchical structure of labels and labels themselves . |
| Approach: | They propose a method that can consider the hierarchical structure of labels and label texts themselves. |
| Outcome: | The proposed method outperforms the methods of the conference participants over the text REtrieval Conference (TREC) 2018 Incident Streams (IS) dataset. |