[HTML][HTML] Knowledge graphs: Opportunities and challenges
With the explosive growth of artificial intelligence (AI) and big data, it has become vitally
important to organize and represent the enormous volume of knowledge appropriately. As …
important to organize and represent the enormous volume of knowledge appropriately. As …
An integrated framework of deep learning and knowledge graph for prediction of stock price trend: An application in Chinese stock exchange market
J Long, Z Chen, W He, T Wu, J Ren - Applied Soft Computing, 2020 - Elsevier
Many studies have been carried out on stock price trend prediction, but most of them
focused on the public market data and did not utilize the trading behaviors owing to the …
focused on the public market data and did not utilize the trading behaviors owing to the …
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 …
City2vec: Urban knowledge discovery based on population mobile network
Due to the needs of social and economic development, population movements between
cities often occur on a large scale. Spontaneous population movements between cities …
cities often occur on a large scale. Spontaneous population movements between cities …
Neural-symbolic integration and the semantic web
Abstract Symbolic Systems in Artificial Intelligence which are based on formal logic and
deductive reasoning are fundamentally different from Artificial Intelligence systems based on …
deductive reasoning are fundamentally different from Artificial Intelligence systems based on …
entity2rec: Property-specific knowledge graph embeddings for item recommendation
Abstract Knowledge graphs have shown to be highly beneficial to recommender systems,
providing an ideal data structure to generate hybrid recommendations using both content …
providing an ideal data structure to generate hybrid recommendations using both content …
The dual echo chamber: Modeling social media polarization for interventional recommending
Echo chambers are social phenomena that amplify agreement and suppress opposing
views in social media which may lead to fragmentation and polarization of the user …
views in social media which may lead to fragmentation and polarization of the user …
Disentangled modeling of social homophily and influence for social recommendation
Social recommendation leverages social information to alleviate data sparsity and cold-start
issues of collaborative filtering (CF) methods. Most existing works model user interests …
issues of collaborative filtering (CF) methods. Most existing works model user interests …
Context-aware graph-based recommendations exploiting personalized pagerank
In this article we present a context-aware recommendation method that exploits graph-
based data models and Personalized PageRank to provide users with recommendations. In …
based data models and Personalized PageRank to provide users with recommendations. In …
Reinforced KGs reasoning for explainable sequential recommendation
We explore the semantic-rich structured information derived from the knowledge graphs
(KGs) associated with the user-item interactions and aim to reason out the motivations …
(KGs) associated with the user-item interactions and aim to reason out the motivations …