Scientific paper recommendation: A survey
Globally, the recommendation services have become important due to the fact that they
support e-commerce applications and different research communities. Recommender …
support e-commerce applications and different research communities. Recommender …
Assessing ranking metrics in top-N recommendation
The evaluation of recommender systems is an area with unsolved questions at several
levels. Choosing the appropriate evaluation metric is one of such important issues. Ranking …
levels. Choosing the appropriate evaluation metric is one of such important issues. Ranking …
[PDF][PDF] A survey of e-commerce recommender systems
F Karimova - European Scientific Journal, 2016 - academia.edu
Due to their powerful personalization and efficiency features, recommendation systems are
being used extensively in many online environments. Recommender systems provide great …
being used extensively in many online environments. Recommender systems provide great …
On the robustness and discriminative power of information retrieval metrics for top-N recommendation
The evaluation of Recommender Systems is still an open issue in the field. Despite its
limitations, offline evaluation usually constitutes the first step in assessing recommendation …
limitations, offline evaluation usually constitutes the first step in assessing recommendation …
A survey of long‐tail item recommendation methods
J Qin - Wireless Communications and Mobile Computing, 2021 - Wiley Online Library
Recommender systems represent a critical field of AI technology applications. The core
function of a recommender system is to recommend items of interest to users, but if it is only …
function of a recommender system is to recommend items of interest to users, but if it is only …
Mitigating long tail effect in recommendations using few shot learning technique
Recommender system has been established as an effective tool for users in providing
personalized suggestions in many domains, especially in e-commerce. In these domains …
personalized suggestions in many domains, especially in e-commerce. In these domains …
CPLR: Collaborative pairwise learning to rank for personalized recommendation
Compared with explicit feedback data, implicit feedback data is easier to be collected and
more widespread. However, implicit feedback data is also more difficult to be analyzed due …
more widespread. However, implicit feedback data is also more difficult to be analyzed due …
An approach to user knowledge acquisition in product design
L Tan, H Zhang - Advanced Engineering Informatics, 2021 - Elsevier
As the world increasingly moves towards a knowledge-based economy, user requirements
become an important factor for enterprises to drive product collaborative design evolution …
become an important factor for enterprises to drive product collaborative design evolution …
Dynamic clustering collaborative filtering recommendation algorithm based on double-layer network
With the rapid development of internet economy, personal recommender system plays an
increasingly important role in e-commerce. In order to improve the quality of …
increasingly important role in e-commerce. In order to improve the quality of …
Effects of sentiment on recommendations in social network
This study adopted a sentiment word database to extract sentiment-related data from
microblog posts. These data were then used to investigate the effect of different types of …
microblog posts. These data were then used to investigate the effect of different types of …