A journey from normative to behavioral operations in supply chain management: A review using Latent Semantic Analysis
This study aims to systematically review the cross disciplinary literature covering the time
period from 1934 to January 2013 on behavioral operations in supply chain in order to …
period from 1934 to January 2013 on behavioral operations in supply chain in order to …
Improving the accuracy of collaborative filtering recommendations using clustering and association rules mining on implicit data
The recommender systems are recently becoming more significant in the age of rapid
development of the Internet technology due to their ability in making a decision to users on …
development of the Internet technology due to their ability in making a decision to users on …
Recommendation as link prediction in bipartite graphs: A graph kernel-based machine learning approach
Recommender systems have been widely adopted in online applications to suggest
products, services, and contents to potential users. Collaborative filtering (CF) is a …
products, services, and contents to potential users. Collaborative filtering (CF) is a …
A combined fuzzy DEMATEL and TOPSIS approach for estimating participants in knowledge-intensive crowdsourcing
Estimating proper participants is an important way to ensure the quality of tasks' outcomes in
knowledge-intensive crowdsourcing (KI-C). The choice of a proper participant is a complex …
knowledge-intensive crowdsourcing (KI-C). The choice of a proper participant is a complex …
Identification of highly-cited papers using topic-model-based and bibliometric features: The consideration of keyword popularity
YH Hu, CT Tai, KE Liu, CF Cai - Journal of Informetrics, 2020 - Elsevier
The number of received citations have been used as an indicator of the impact of academic
publications. Developing tools to find papers that have the potential to become highly-cited …
publications. Developing tools to find papers that have the potential to become highly-cited …
An improved collaborative filtering method based on similarity
J Feng, X Fengs, N Zhang, J Peng - PloS one, 2018 - journals.plos.org
The recommender system is widely used in the field of e-commerce and plays an important
role in guiding customers to make smart decisions. Although many algorithms are available …
role in guiding customers to make smart decisions. Although many algorithms are available …
A survey on data mining techniques in recommender systems
Recommender systems have been regarded as gaining a more significant role with the
emergence of the first research article on collaborative filtering (CF) in the mid-1990s. CF …
emergence of the first research article on collaborative filtering (CF) in the mid-1990s. CF …
Providing item-side individual fairness for deep recommender systems
X Wang, WH Wang - Proceedings of the 2022 ACM Conference on …, 2022 - dl.acm.org
Recent advent of deep learning techniques have reinforced the development of new
recommender systems. Although these systems have been demonstrated as efficient and …
recommender systems. Although these systems have been demonstrated as efficient and …
Exploring user movie interest space: A deep learning based dynamic recommendation model
M Gan, H Cui - Expert Systems with Applications, 2021 - Elsevier
Exploring user interest behind massive user behaviors is essential for online
recommendations. Although recommendation models have been proposed recently with …
recommendations. Although recommendation models have been proposed recently with …
Content-oriented user modeling for personalized response ranking in chatbots
Automatic chatbots (also known as chat-agents) have attracted much attention from both
researching and industrial fields. Generally, the semantic relevance between users' queries …
researching and industrial fields. Generally, the semantic relevance between users' queries …