Abstract
In this paper, we propose a moral judgment system. Moral judgment means right and wrong judgment. The proposed system consists of the learning phase and the moral judgment phase. In the learning phase, the positive words and the negative words (evaluation expressions) are extracted based on the cooccurrence frequency of the learning data and the words in the polarity dictionary. Then, the words having high score are extracted. They are used to calculate the score. In the moral judgment phase, first, the determination of whether the input sentence relates to morality or not is performed. Second, if the input is determined to relate to morality, the scoring based on the co-occurrence frequency of the input and the important evaluation expressions is conducted. At this point, when the number of words in the input sentence is large, moral judgment is difficult. In such a case, such sentences are simplified based on the TF-IDF method. In the experiments, we compared the moral judgment by the system and by human. As a result, the effectiveness of the proposed system is confirmed.
Original language | English |
---|---|
Title of host publication | 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 1040-1047 |
Number of pages | 8 |
ISBN (Print) | 9781479959556 |
DOIs | |
Publication status | Published - 2014 Feb 18 |
Event | 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014 - Kitakyushu, Japan Duration: 2014 Dec 3 → 2014 Dec 6 |
Other
Other | 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014 |
---|---|
Country/Territory | Japan |
City | Kitakyushu |
Period | 14/12/3 → 14/12/6 |
ASJC Scopus subject areas
- Software
- Artificial Intelligence