Although nonnegative matrix factorization (NMF) is widely used, some matrix factorization
methods result in misleading results and waste of computing resources due to lack of timely …

Graph non-negative matrix factorization (GNMF) can discover the data's intrinsic low-
dimensional structure embedded in the high-dimensional space. So, it has superior …

Regularly checking the situation is essential for improving road safety and boosting
economic development. To this end, this study incorporates techniques in the three stages …

Contemporary technologies have ensured the availability of high‐quality research data
shared over the Internet. This has resulted in a tremendous availability of research literature …

In order to investigate the key attributes of casino hotel customer eWOM and their structural
relationships, this study selects two casino hotels located in Las Vegas and Macao. Through …

The initial dimensions extracted by latent semantic analysis (LSA) of a document-term matrix
have been shown to mainly display marginal effects, which are irrelevant for information …

Recently, the proposed non-parametric Bayesian based techniques which aim to model
short-length textual documents through the multinomial distribution on the bag-of-words …

Text clustering has been an overlooked field of text mining that requires more attention.
Several applications require automatic text organisation which relies on an information …

Text mining is a new branch of AI that employs natural language processing techniques to
convert unstructured text into a structured format for easier comprehension. It is becoming …

Kernel nonnegative matrix factorization (KNMF) has emerged as a promising nonlinear data
representation method, especially for applications with small sample sizes. Existing methods …