The evolution of topic modeling
R Churchill, L Singh - ACM Computing Surveys, 2022 - dl.acm.org
Topic models have been applied to everything from books to newspapers to social media
posts in an effort to identify the most prevalent themes of a text corpus. We provide an in …
posts in an effort to identify the most prevalent themes of a text corpus. We provide an in …
Explanation mining: Post hoc interpretability of latent factor models for recommendation systems
G Peake, J Wang - Proceedings of the 24th ACM SIGKDD International …, 2018 - dl.acm.org
The widescale use of machine learning algorithms to drive decision-making has highlighted
the critical importance of ensuring the interpretability of such models in order to engender …
the critical importance of ensuring the interpretability of such models in order to engender …
Analyzing user reviews in tourism with topic models
User generated content in general and textual reviews in particular constitute a vast source
of information for the decision making of tourists and management and are therefore a key …
of information for the decision making of tourists and management and are therefore a key …
Linked open data-based explanations for transparent recommender systems
In this article we propose a framework that generates natural language explanations
supporting the suggestions generated by a recommendation algorithm. The cornerstone of …
supporting the suggestions generated by a recommendation algorithm. The cornerstone of …
Scalable and interpretable product recommendations via overlapping co-clustering
We consider the problem of generating interpretable recommendations by identifying
overlapping co-clusters of clients and products, based only on positive or implicit feedback …
overlapping co-clusters of clients and products, based only on positive or implicit feedback …
A 3D item space visualization for presenting and manipulating user preferences in collaborative filtering
While conventional Recommender Systems perform well in automatically generating
personalized suggestions, it is often difficult for users to understand why certain items are …
personalized suggestions, it is often difficult for users to understand why certain items are …
The number of topics optimization: Clustering approach
F Krasnov, A Sen - Machine Learning and Knowledge Extraction, 2019 - mdpi.com
Although topic models have been used to build clusters of documents for more than ten
years, there is still a problem of choosing the optimal number of topics. The authors …
years, there is still a problem of choosing the optimal number of topics. The authors …
Effects of preprocessing and training biases in latent factor models for recommender systems
Latent factor (LF)-based models are highly efficient in addressing high-dimensional and
sparse (HiDS) matrices raised in big-data-related applications like recommender systems …
sparse (HiDS) matrices raised in big-data-related applications like recommender systems …
Understanding global research trends in the control and prevention of infectious diseases for children: Insights from text mining and topic modeling
WO Oh, E Lee, Y Heo, MJ Jung… - Journal of Nursing …, 2024 - Wiley Online Library
Introduction The emergence of novel infectious diseases has amplified the urgent need for
effective prevention strategies, especially ones targeting vulnerable populations such as …
effective prevention strategies, especially ones targeting vulnerable populations such as …
Explanations and user control in recommender systems
1 BACKGROUND The personalized selection and presentation of content have become
common in today's online world, for example on media streaming sites, e-commerce shops …
common in today's online world, for example on media streaming sites, e-commerce shops …