Name
Abstract | ||
|---|---|---|
A novel intelligent interface eases the browsing of Web documents written in the second languages of users. It automatically predicts words unfamiliar to the user by a collective intelligence method and glosses them with their meaning in advance. If the prediction succeeds, the user does not need to consult a dictionary; even if it fails, the user can correct the prediction. The correction data are collected and used to improve the accuracy of further predictions. The prediction is personalized in that every user's language ability is estimated by a state-of-the-art language testing model, which is trained in a practical response time with only a small sacrifice of prediction accuracy. The system was evaluated in terms of prediction accuracy and reading simulation. The reading simulation results show that this system can reduce the number of clicks for most readers with insufficient vocabulary to read documents and can significantly reduce the remaining number of unfamiliar words after the prediction and glossing for all users. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1145/2438653.2438666 | ACM TIST |
Keywords | Field | DocType |
unfamiliar word,second-language web document,correction data,web document,reading simulation result,prediction accuracy,collective intelligence method,state-of-the-art language testing model,remaining number,personalized reading support,insufficient vocabulary,language ability,item response theory,web pages,logistic regression | Data mining,Web page,Collective intelligence,Intelligent interface,Computer science,Second language,Artificial intelligence,Language assessment,Vocabulary,Item response theory,Machine learning | Journal |
Volume | Issue | ISSN |
4 | 2 | 2157-6904 |
Citations | PageRank | References |
2 | 0.42 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yo Ehara | 1 | 12 | 6.31 |
| Nobuyuki Shimizu | 2 | 37 | 7.76 |
| Takashi Ninomiya | 3 | 214 | 21.52 |
| Hiroshi Nakagawa | 4 | 390 | 40.38 |