A survey of app store analysis for software engineering
App Store Analysis studies information about applications obtained from app stores. App
stores provide a wealth of information derived from users that would not exist had the …
stores provide a wealth of information derived from users that would not exist had the …
Latent Dirichlet allocation (LDA) and topic modeling: models, applications, a survey
Topic modeling is one of the most powerful techniques in text mining for data mining, latent
data discovery, and finding relationships among data and text documents. Researchers …
data discovery, and finding relationships among data and text documents. Researchers …
Mining smartphone data for app usage prediction and recommendations: A survey
H Cao, M Lin - Pervasive and Mobile Computing, 2017 - Elsevier
Smartphones nowadays have become indispensable personal gadgets to support our
activities in almost every aspect of our lives. Thanks to the tremendous advancement of …
activities in almost every aspect of our lives. Thanks to the tremendous advancement of …
Consisrec: Enhancing gnn for social recommendation via consistent neighbor aggregation
Social recommendation aims to fuse social links with user-item interactions to alleviate the
cold-start problem for rating prediction. Recent developments of Graph Neural Networks …
cold-start problem for rating prediction. Recent developments of Graph Neural Networks …
[PDF][PDF] Cross-domain recommendation: An embedding and map** approach.
Data sparsity is one of the most challenging problems for recommender systems. One
promising solution to this problem is cross-domain recommendation, ie, leveraging …
promising solution to this problem is cross-domain recommendation, ie, leveraging …
Warm up cold-start advertisements: Improving ctr predictions via learning to learn id embeddings
Click-through rate (CTR) prediction has been one of the most central problems in
computational advertising. Lately, embedding techniques that produce low-dimensional …
computational advertising. Lately, embedding techniques that produce low-dimensional …
From zero-shot learning to cold-start recommendation
Zero-shot learning (ZSL) and cold-start recommendation (CSR) are two challenging
problems in computer vision and recommender system, respectively. In general, they are …
problems in computer vision and recommender system, respectively. In general, they are …
Connecting social media to e-commerce: Cold-start product recommendation using microblogging information
In recent years, the boundaries between e-commerce and social networking have become
increasingly blurred. Many e-commerce Web sites support the mechanism of social login …
increasingly blurred. Many e-commerce Web sites support the mechanism of social login …
Rating‐Based Recommender System Based on Textual Reviews Using IoT Smart Devices
Recommender system (RS) is a unique type of information clarification system that
anticipates the user's evaluation of items from a large pool based on the expectations of a …
anticipates the user's evaluation of items from a large pool based on the expectations of a …
Predicting the next app that you are going to use
Given the large number of installed apps and the limited screen size of mobile devices, it is
often tedious for users to search for the app they want to use. Although some mobile OSs …
often tedious for users to search for the app they want to use. Although some mobile OSs …