Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Smartphone app usage analysis: datasets, methods, and applications
As smartphones have become indispensable personal devices, the number of smartphone
users has increased dramatically over the last decade. These personal devices, which are …
users has increased dramatically over the last decade. These personal devices, which are …
Current trends in collaborative filtering recommendation systems
SA Amin, J Philips, N Tabrizi - … 2019: 15th World Congress, Held as Part of …, 2019 - Springer
Many different approaches for designing recommendation systems exist, including
collaborative filtering, content-based, and hybrid approaches. Following an overview of …
collaborative filtering, content-based, and hybrid approaches. Following an overview of …
MPAN: Multi-parallel attention network for session-based recommendation
A powerful session-based recommender can typically explore the users' evolving interests
(ie, a combination of her long-term and short-term interests). Recent advances in attention …
(ie, a combination of her long-term and short-term interests). Recent advances in attention …
SAppKG: mobile app recommendation using knowledge graph and side information-a secure framework
Due to the rapid development of technology and the widespread usage of smartphones, the
number of mobile applications is exponentially growing. Finding a suitable collection of apps …
number of mobile applications is exponentially growing. Finding a suitable collection of apps …
Personalized context-aware collaborative online activity prediction
With the rapid development of Internet services and mobile devices, nowadays, users can
connect to online services anytime and anywhere. Naturally, user's online activity behavior …
connect to online services anytime and anywhere. Naturally, user's online activity behavior …
DeepApp: characterizing dynamic user interests for mobile application recommendation
It is extremely difficult to find one app in app stores that exactly meets the needs of users with
the boom in mobile applications nowadays. Although numerous app recommendation …
the boom in mobile applications nowadays. Although numerous app recommendation …
Understanding the long-term dynamics of mobile app usage context via graph embedding
With the increasing diversity of mobile apps, users install many apps in their smartphones
and often use several apps together to meet a specific requirement. Because of the …
and often use several apps together to meet a specific requirement. Because of the …
CFDIL: a context-aware feature deep interaction learning for app recommendation
Q Hao, K Zhu, C Wang, P Wang, X Mo, Z Liu - Soft Computing, 2022 - Springer
The rapid development of mobile Internet has spawned various mobile applications (apps).
A large number of apps make it difficult for users to choose apps conveniently, causing the …
A large number of apps make it difficult for users to choose apps conveniently, causing the …
A knowledge graph based approach for mobile application recommendation
With the rapid prevalence of mobile devices and the dramatic proliferation of mobile
applications (apps), app recommendation becomes an emergent task that would benefit …
applications (apps), app recommendation becomes an emergent task that would benefit …
[HTML][HTML] Graph-based method for app usage prediction with attributed heterogeneous network embedding
Y Zhou, S Li, Y Liu - Future Internet, 2020 - mdpi.com
Smartphones and applications have become widespread more and more. Thus, using the
hardware and software of users' mobile phones, we can get a large amount of personal …
hardware and software of users' mobile phones, we can get a large amount of personal …