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Predicting Next-use Mobile Apps Using App Semantic Representations
https://ipsj.ixsq.nii.ac.jp/records/213299
https://ipsj.ixsq.nii.ac.jp/records/213299b209afdc-d2e2-4c09-8686-59304181552f
| 名前 / ファイル | ライセンス | アクション |
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IPSJ-JNL6210004.pdf (1.4 MB)
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Copyright (c) 2021 by the Information Processing Society of Japan
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| オープンアクセス | ||
| Item type | Journal(1) | |||||||||||||
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| 公開日 | 2021-10-15 | |||||||||||||
| タイトル | ||||||||||||||
| タイトル | Predicting Next-use Mobile Apps Using App Semantic Representations | |||||||||||||
| タイトル | ||||||||||||||
| 言語 | en | |||||||||||||
| タイトル | Predicting Next-use Mobile Apps Using App Semantic Representations | |||||||||||||
| 言語 | ||||||||||||||
| 言語 | eng | |||||||||||||
| キーワード | ||||||||||||||
| 主題Scheme | Other | |||||||||||||
| 主題 | [特集：ユビキタスコンピューティングシステム（X）] smartphone, mobile apps, next-use app prediction, pattern recognition | |||||||||||||
| 資源タイプ | ||||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||||||
| 資源タイプ | journal article | |||||||||||||
| 著者所属 | ||||||||||||||
| Graduate School of Information Science and Technology, Osaka University | ||||||||||||||
| 著者所属 | ||||||||||||||
| Graduate School of Information Science and Technology, Osaka University | ||||||||||||||
| 著者所属 | ||||||||||||||
| Graduate School of Information Science and Technology, Osaka University | ||||||||||||||
| 著者所属 | ||||||||||||||
| Graduate School of Information Science and Technology, Osaka University | ||||||||||||||
| 著者所属(英) | ||||||||||||||
| en | ||||||||||||||
| Graduate School of Information Science and Technology, Osaka University | ||||||||||||||
| 著者所属(英) | ||||||||||||||
| en | ||||||||||||||
| Graduate School of Information Science and Technology, Osaka University | ||||||||||||||
| 著者所属(英) | ||||||||||||||
| en | ||||||||||||||
| Graduate School of Information Science and Technology, Osaka University | ||||||||||||||
| 著者所属(英) | ||||||||||||||
| en | ||||||||||||||
| Graduate School of Information Science and Technology, Osaka University | ||||||||||||||
| 著者名 |
Cheng, Chen
× Cheng, Chen
× Takuya, Maekawa
× Daichi, Amagata
× Takahiro, Hara
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| 著者名(英) |
Cheng, Chen
× Cheng, Chen
× Takuya, Maekawa
× Daichi, Amagata
× Takahiro, Hara
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| 論文抄録 | ||||||||||||||
| 内容記述タイプ | Other | |||||||||||||
| 内容記述 | Using the app usage history of a target user as a basis, this study proposes a novel method for predicting next-use mobile apps of the user that can assist the user in selecting an app from a list of installed apps. The proposed method is designed to train a next-use app prediction model using semantic representations of the usage histories of other users (source users) to deal with the user and app cold-start problems of an app prediction system in which training data from a target user beginning to use the system and training data related to newly installed or released apps are considered to be insufficient. We predict the usage of apps by a target user by leveraging the semantic similarities between the apps that are installed on the smartphones of the source users and the apps that are installed on the smartphone of a target user, permitting us to predict next-use apps regardless of the apps installed in the target user's smartphone. We evaluate our method using the actual app usage data collected from 100 participants over a period of approximately 70 days with 300,000 app usage histories. ------------------------------ This is a preprint of an article intended for publication Journal of Information Processing(JIP). This preprint should not be cited. This article should be cited as: Journal of Information Processing Vol.29(2021) (online) DOI http://dx.doi.org/10.2197/ipsjjip.29.597 ------------------------------ |
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| 論文抄録(英) | ||||||||||||||
| 内容記述タイプ | Other | |||||||||||||
| 内容記述 | Using the app usage history of a target user as a basis, this study proposes a novel method for predicting next-use mobile apps of the user that can assist the user in selecting an app from a list of installed apps. The proposed method is designed to train a next-use app prediction model using semantic representations of the usage histories of other users (source users) to deal with the user and app cold-start problems of an app prediction system in which training data from a target user beginning to use the system and training data related to newly installed or released apps are considered to be insufficient. We predict the usage of apps by a target user by leveraging the semantic similarities between the apps that are installed on the smartphones of the source users and the apps that are installed on the smartphone of a target user, permitting us to predict next-use apps regardless of the apps installed in the target user's smartphone. We evaluate our method using the actual app usage data collected from 100 participants over a period of approximately 70 days with 300,000 app usage histories. ------------------------------ This is a preprint of an article intended for publication Journal of Information Processing(JIP). This preprint should not be cited. This article should be cited as: Journal of Information Processing Vol.29(2021) (online) DOI http://dx.doi.org/10.2197/ipsjjip.29.597 ------------------------------ |
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| 書誌レコードID | ||||||||||||||
| 収録物識別子タイプ | NCID | |||||||||||||
| 収録物識別子 | AN00116647 | |||||||||||||
| 書誌情報 |
情報処理学会論文誌 巻 62, 号 10, 発行日 2021-10-15 |
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| ISSN | ||||||||||||||
| 収録物識別子タイプ | ISSN | |||||||||||||
| 収録物識別子 | 1882-7764 | |||||||||||||
