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- W2034796557 abstract "The remarkable development of IT is contributed to popularization of smart phones, which in turn creates a new domain called app store. Smartphone apps have grown fast because they can be easily purchased through an app store. As the volume of apps traded in app stores is so huge that it is extremely hard for users to find the exact app they want. In general, an app store recommends an app to users based on the search words they entered. In terms of recommendation of app, this kind of content-based method is not effective. To increase accuracy in recommending app, this paper proposes a characteristic similarity-based app recommendation method. This method creates attributes on the app based on the related information such as genre, functionality and number of downloads and then compares them with the propensity to use the app. According to diverse simulations, the method proposed in this paper improved the performance of app recommendation by 33% in average, compared to the conventional method." @default.
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- W2034796557 date "2012-12-31" @default.
- W2034796557 modified "2023-09-24" @default.
- W2034796557 title "App Recommendation Based on Characteristic Similarity" @default.
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- W2034796557 doi "https://doi.org/10.9728/dcs.2012.13.4.559" @default.
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