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 …
[HTML][HTML] Non-iid recommender systems: A review and framework of recommendation paradigm shifting
L Cao - Engineering, 2016 - Elsevier
While recommendation plays an increasingly critical role in our living, study, work, and
entertainment, the recommendations we receive are often for irrelevant, duplicate, or …
entertainment, the recommendations we receive are often for irrelevant, duplicate, or …
A method for mixed data classification base on RBF-ELM network
Q Li, Q Xiong, S Ji, Y Yu, C Wu, H Yi - Neurocomputing, 2021 - Elsevier
The classification tasks for numerical or categorical data have been well developed.
However, the data collected in the real world are frequently the mixed type containing …
However, the data collected in the real world are frequently the mixed type containing …
[图书][B] Preference-based spatial co-location pattern mining
L Wang, Y Fang, L Zhou - 2022 - Springer
The development of information technology has enabled many different technologies to
collect large amounts of spatial data every day. It is of very great significance to discover …
collect large amounts of spatial data every day. It is of very great significance to discover …
Unsupervised heterogeneous coupling learning for categorical representation
Complex categorical data is often hierarchically coupled with heterogeneous relationships
between attributes and attribute values and the couplings between objects. Such value-to …
between attributes and attribute values and the couplings between objects. Such value-to …
Outlier detection in complex categorical data by modeling the feature value couplings
This paper introduces a novel unsupervised outlier detection method, namely Coupled
Biased Random Walks (CBRW), for identifying outliers in categorical data with diversified …
Biased Random Walks (CBRW), for identifying outliers in categorical data with diversified …
Incremental semi-supervised extreme learning machine for mixed data stream classification
With an explosive growth of data generated in the Internet and other fields, the data stream
classification has sparked broad interest recently. Nowadays, some of the challenges in data …
classification has sparked broad interest recently. Nowadays, some of the challenges in data …
Cure: Flexible categorical data representation by hierarchical coupling learning
The representation of categorical data with hierarchical value coupling relationships (ie,
various value-to-value cluster interactions) is very critical yet challenging for capturing …
various value-to-value cluster interactions) is very critical yet challenging for capturing …
Concept representation by learning explicit and implicit concept couplings
Generating the precise semantic representation of a word or concept is a fundamental task
in natural language processing. Recent studies which incorporate semantic knowledge into …
in natural language processing. Recent studies which incorporate semantic knowledge into …
Attributes coupling based matrix factorization for item recommendation
Recommender systems have attracted lots of attention since they alleviate the information
overload problem for users. Matrix factorization is one of the most widely employed …
overload problem for users. Matrix factorization is one of the most widely employed …