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ホウチン テルヒサ
Teruhisa Hochin
寶珍 輝尚 所属 追手門学院大学 理工学部 情報工学科 職種 教授 |
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| 発行・発表の年月 | 2022/12 |
| 形態種別 | 論文 |
| 査読 | 査読あり |
| 標題 | Application of 2‑gram and 3‑gram to Obtain Factor Scores of Statements Posted at Q&A Sites |
| 執筆形態 | 共著・編著（代表編著を除く） |
| 掲載誌名 | International Journal of Networked and Distributed Computing |
| 掲載区分 | 国外 |
| 巻・号・頁 | 10(1-2),11-20頁 |
| 著者・共著者 | Yuya Yokoyama,Teruhisa Hochin,Hiroki Nomiya |
| 概要 | With a view to solving the mismatches between the ideas of questioners and respondents of Question and Answer (Q&A) sites, impression evaluation experiments have resulted in obtaining nine factors of impressions. Then through multiple regression analysis factor scores have been estimated by utilizing the feature values of statements, such as syntactic information, etc. Those factor scores calculated were subsequently employed for inspecting their potential to detect respondents who are expected and likely to appropriately answer a newly posted question. Nevertheless, our method so far has largely depended on the syntactic information extracted through morphological analysis. Moreover, the number of explanatory variables utilized for obtaining factor scores has been appreciably extravagant and complex. Thus, instead of morphological analysis, 2-gram was applied to the explanatory variables to estimate factor scores. The analysis result with the application of 2-gram has led to greater estimation accuracy than the case of morphological analysis for all nine factors. For further perception and comparison, in this paper, 3-gram was applied to the feature values in place of 2-gram or morphological analysis, in a similar fashion as the previous analysis using 2-gram. Further analysis has shown that 2-gram and 3-gram outperform morphological analysis in terms of estimation accuracy. Comparing the results for the nine factors, 2-gram showed the best results. It could also be suggested that a mere 2-gram or 3-gram would be sufficient in applying N-gram as syntactic information of the feature values to estimate factor scores. |
| DOI | 10.1007/s44227-022-00005-2 |
| ISSN | 2211-7938/2211-7946 |