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| Content Provider | ACM Digital Library |
|---|---|
| Author | Onizuka, Makoto Kazui, Hiroaki Kosugi, Naoko Nakajima, Hisae Ikeda, Manabu |
| Abstract | This paper proposes a grouping technique of sentences that contain dementia care information and describes analytical results of statistical information which influences the grouping. This paper focuses on the grouping of the "incidents" in sentences. One of the problems to group the incidents is that the sentences input by caregivers are redundant. In other words, the sentences contain care information which were related to the incidents, but were unnecessary for the grouping. In order to extract the incident information from the sentences, we divide them into sub-sentences for every verbs and auxiliary verbs. Similarities among sub-sentences are used for the grouping and the accuracy is evaluated with the precision. As a result, we found that a sub-sentence containing seven words is good for the grouping. |
| Starting Page | 477 |
| Ending Page | 481 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781450348072 |
| DOI | 10.1145/3011141.3011210 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2016-11-28 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Word2vec Text mining Sentence vector Dementia care text information |
| Content Type | Text |
| Resource Type | Article |
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