A comprehensive survey of knowledge graph-based recommender systems: Technologies, development, and contributions
J Chicaiza, P Valdiviezo-Diaz - Information, 2021 - mdpi.com
In recent years, the use of recommender systems has become popular on the web. To
improve recommendation performance, usage, and scalability, the research has evolved by …
improve recommendation performance, usage, and scalability, the research has evolved by …
Categorization of knowledge graph based recommendation methods and benchmark datasets from the perspectives of application scenarios: A comprehensive …
Recommender Systems (RS) are established to deal with the preferences of users to
enhance their experience and interest in innumerable online applications by streamlining …
enhance their experience and interest in innumerable online applications by streamlining …
Learning with memory embeddings
Embedding learning, aka representation learning, has been shown to be able to model
large-scale semantic knowledge graphs. A key concept is a mapping of the knowledge …
large-scale semantic knowledge graphs. A key concept is a mapping of the knowledge …
Configuration of industrial automation solutions using multi-relational recommender systems
M Hildebrandt, SS Sunder, S Mogoreanu… - Machine Learning and …, 2019 - Springer
Building complex automation solutions, common to process industries and building
automation, requires the selection of components early on in the engineering process …
automation, requires the selection of components early on in the engineering process …
Enhancing representation learning with tensor decompositions for knowledge graphs and high dimensional sequence modeling
Y Yang - 2018 - edoc.ub.uni-muenchen.de
The capability of processing and digesting raw data is one of the key features of a human-
like artificial intelligence system. For instance, real-time machine translation should be able …
like artificial intelligence system. For instance, real-time machine translation should be able …