{"title":"智能手机传感器与用户使用智能手机意图的调查","authors":"Priyanka Bhatele, Dr Mangesh Bedekar","doi":"10.1109/I2CT57861.2023.10126192","DOIUrl":null,"url":null,"abstract":"Smartphone/Tablet users are approximately 3 million all over the world. It is likely to increase by several 100 million in the next few years. Around 40% of these users read online. Explicit means of feedback system is strongly based. It provides the most accuracy when rating an online learning application. Increase in the availability of content over the web and high user engagements, has led to the demand of the means that implicitly provide feedback. Implicit feedback relies on understanding the quality of the content based on the user activities performed over the web applications. Less accuracy is the limitation. It needs to stand with a support to provide as strong base as the explicit model does. Clipboard copy operations on the webpage provide an implicit insight to the user intentions. Screen activities like scrolling and pinch to zoom further can statistically be proven the positive indicators of user interest. Smartphone sensors like Gyroscope and Accelerometer silently sense human screen activities and mobile gestures. This review paper is based on the understanding of smartphone sensors and the inferences of user intent through it. The dig is based on various implicit indicators like mobile gestures, smartphone sensors and clipboard copy operations.","PeriodicalId":150346,"journal":{"name":"2023 IEEE 8th International Conference for Convergence in Technology (I2CT)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Survey on Smartphone Sensors and User Intent in Smartphone Usage\",\"authors\":\"Priyanka Bhatele, Dr Mangesh Bedekar\",\"doi\":\"10.1109/I2CT57861.2023.10126192\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Smartphone/Tablet users are approximately 3 million all over the world. It is likely to increase by several 100 million in the next few years. Around 40% of these users read online. Explicit means of feedback system is strongly based. It provides the most accuracy when rating an online learning application. Increase in the availability of content over the web and high user engagements, has led to the demand of the means that implicitly provide feedback. Implicit feedback relies on understanding the quality of the content based on the user activities performed over the web applications. Less accuracy is the limitation. It needs to stand with a support to provide as strong base as the explicit model does. Clipboard copy operations on the webpage provide an implicit insight to the user intentions. Screen activities like scrolling and pinch to zoom further can statistically be proven the positive indicators of user interest. Smartphone sensors like Gyroscope and Accelerometer silently sense human screen activities and mobile gestures. This review paper is based on the understanding of smartphone sensors and the inferences of user intent through it. The dig is based on various implicit indicators like mobile gestures, smartphone sensors and clipboard copy operations.\",\"PeriodicalId\":150346,\"journal\":{\"name\":\"2023 IEEE 8th International Conference for Convergence in Technology (I2CT)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE 8th International Conference for Convergence in Technology (I2CT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/I2CT57861.2023.10126192\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE 8th International Conference for Convergence in Technology (I2CT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/I2CT57861.2023.10126192","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Survey on Smartphone Sensors and User Intent in Smartphone Usage
Smartphone/Tablet users are approximately 3 million all over the world. It is likely to increase by several 100 million in the next few years. Around 40% of these users read online. Explicit means of feedback system is strongly based. It provides the most accuracy when rating an online learning application. Increase in the availability of content over the web and high user engagements, has led to the demand of the means that implicitly provide feedback. Implicit feedback relies on understanding the quality of the content based on the user activities performed over the web applications. Less accuracy is the limitation. It needs to stand with a support to provide as strong base as the explicit model does. Clipboard copy operations on the webpage provide an implicit insight to the user intentions. Screen activities like scrolling and pinch to zoom further can statistically be proven the positive indicators of user interest. Smartphone sensors like Gyroscope and Accelerometer silently sense human screen activities and mobile gestures. This review paper is based on the understanding of smartphone sensors and the inferences of user intent through it. The dig is based on various implicit indicators like mobile gestures, smartphone sensors and clipboard copy operations.