A survey on session-based recommender systems
Recommender systems (RSs) have been playing an increasingly important role for informed
consumption, services, and decision-making in the overloaded information era and digitized …
consumption, services, and decision-making in the overloaded information era and digitized …
Cross-domain recommendation: challenges, progress, and prospects
To address the long-standing data sparsity problem in recommender systems (RSs), cross-
domain recommendation (CDR) has been proposed to leverage the relatively richer …
domain recommendation (CDR) has been proposed to leverage the relatively richer …
Are we really making much progress? A worrying analysis of recent neural recommendation approaches
Deep learning techniques have become the method of choice for researchers working on
algorithmic aspects of recommender systems. With the strongly increased interest in …
algorithmic aspects of recommender systems. With the strongly increased interest in …
[ΒΙΒΛΙΟ][B] Neural networks and deep learning
CC Aggarwal - 2018 - Springer
“Any AI smart enough to pass a Turing test is smart enough to know to fail it.”–*** Ian
McDonald Neural networks were developed to simulate the human nervous system for …
McDonald Neural networks were developed to simulate the human nervous system for …
Where to go next: A spatio-temporal gated network for next poi recommendation
Next Point-of-Interest (POI) recommendation which is of great value to both users and POI
holders is a challenging task since complex sequential patterns and rich contexts are …
holders is a challenging task since complex sequential patterns and rich contexts are …
xdeepfm: Combining explicit and implicit feature interactions for recommender systems
Combinatorial features are essential for the success of many commercial models. Manually
crafting these features usually comes with high cost due to the variety, volume and velocity …
crafting these features usually comes with high cost due to the variety, volume and velocity …
DKN: Deep knowledge-aware network for news recommendation
Online news recommender systems aim to address the information explosion of news and
make personalized recommendation for users. In general, news language is highly …
make personalized recommendation for users. In general, news language is highly …
Neural attentive session-based recommendation
Given e-commerce scenarios that user profiles are invisible, session-based
recommendation is proposed to generate recommendation results from short sessions …
recommendation is proposed to generate recommendation results from short sessions …
Multimodal intelligence: Representation learning, information fusion, and applications
Deep learning methods haverevolutionized speech recognition, image recognition, and
natural language processing since 2010. Each of these tasks involves a single modality in …
natural language processing since 2010. Each of these tasks involves a single modality in …
Deep learning based recommender system: A survey and new perspectives
With the growing volume of online information, recommender systems have been an
effective strategy to overcome information overload. The utility of recommender systems …
effective strategy to overcome information overload. The utility of recommender systems …