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2016 | OriginalPaper | Buchkapitel

Scrutinizing Mobile App Recommendation: Identifying Important App-Related Indicators

verfasst von : Jovian Lin, Kazunari Sugiyama, Min-Yen Kan, Tat-Seng Chua

Erschienen in: Information Retrieval Technology

Verlag: Springer International Publishing

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Abstract

Among several traditional and novel mobile app recommender techniques that utilize a diverse set of app-related features (such as an app’s Twitter followers, various version instances, etc.), which app-related features are the most important indicators for app recommendation? In this paper, we develop a hybrid app recommender framework that integrates a variety of app-related features and recommendation techniques, and then identify the most important indicators for the app recommendation task. Our results reveal an interesting correlation with data from third-party app analytics companies; and suggest that, in the context of mobile app recommendation, more focus could be placed in user and trend analysis via social networks.

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Titel: Scrutinizing Mobile App Recommendation: Identifying Important App-Related Indicators
verfasst von: Jovian Lin
Kazunari Sugiyama
Min-Yen Kan
Tat-Seng Chua
Verlag: Springer International Publishing
Buch: Information Retrieval Technology
Print ISBN: 978-3-319-48050-3

Electronic ISBN: 978-3-319-48051-0

Copyright-Jahr: 2016
DOI: https://doi.org/10.1007/978-3-319-48051-0_15

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