| Item type |
National Convention(1) |
| 公開日 |
2019-02-28 |
| タイトル |
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タイトル |
深層学習を用いたVOCに基づいた顧客の退会危険度推定 |
| 言語 |
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言語 |
jpn |
| キーワード |
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主題Scheme |
Other |
|
主題 |
人工知能と認知科学 |
| 資源タイプ |
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資源タイプ識別子 |
http://purl.org/coar/resource_type/c_5794 |
|
資源タイプ |
conference paper |
| 著者所属 |
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|
明大 |
| 著者所属 |
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明大 |
| 著者所属 |
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|
西武文理大 |
| 著者所属 |
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|
電機大 |
| 著者名 |
川崎, 雄大
櫻井, 義尚
櫻井, 恵里子
鶴田, 節夫
|
| 論文抄録 |
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内容記述タイプ |
Other |
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内容記述 |
In recent years, the scale of E-commerce web sites and the number of users have increased remarkably. Along with that, it is required to respond promptly to requests from customers via online. In this research, we identify costumers, who want to withdraw their order by analyzing their e-mail text sent to customer support for classification model to urge operators to respond. The classification model was carried out in a convolution neural network after embedding expressions of words. We tuned the parameters in the experiment and found it possible to classify with accuracy of 79.2%. In addition, we compared the accuracy with predictive model by customer status. As a result, we obtained high accuracy compared with logistic regression models and support vector machines. From these results, it was proven that the mail document contained information indicating to resign from EC site customers. |
| 書誌レコードID |
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収録物識別子タイプ |
NCID |
|
収録物識別子 |
AN00349328 |
| 書誌情報 |
第81回全国大会講演論文集
巻 2019,
号 1,
p. 127-128,
発行日 2019-02-28
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| 出版者 |
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言語 |
ja |
|
出版者 |
情報処理学会 |
IPSJ-Z81-6Q-03.pdf (429.6 kB)
