A clustering method based on multi-positive–negative granularity and attenuation-diffusion pattern
As an important part of machine learning, clustering methods have been continuously paid
attention to. Current clustering methods divide data objects usually based on Euclidean …
attention to. Current clustering methods divide data objects usually based on Euclidean …
Generic metadata representation framework for social-based event detection, description, and linkage
Various methods have been put forward to perform automatic social-based event detection
and description. Yet, most of them do not capture the semantic meaning embedded in online …
and description. Yet, most of them do not capture the semantic meaning embedded in online …
An observational analysis of the trope “A p-value of< 0.05 was considered statistically significant” and other cut-and-paste statistical methods
Appropriate descriptions of statistical methods are essential for evaluating research quality
and reproducibility. Despite continued efforts to improve reporting in publications …
and reproducibility. Despite continued efforts to improve reporting in publications …
Big data analytics of social network marketing and personalized recommendations
SH Liao, CA Yang - Social Network Analysis and Mining, 2021 - Springer
A fan page is a kind of a social network. Social network marketing (SNM) is a form of Internet
marketing involving the creation and sharing of content on social media networks to achieve …
marketing involving the creation and sharing of content on social media networks to achieve …
Identifying Covid-19 misinformation tweets and learning their spatio-temporal topic dynamics using Nonnegative Coupled Matrix Tensor Factorization
Social media platforms like Twitter have become an easy portal for billions of people to
connect and exchange their thoughts. Unfortunately, people commonly use these platforms …
connect and exchange their thoughts. Unfortunately, people commonly use these platforms …
Fine-grained algorithm for improving knn computational performance on clinical trials text classification
J Jasmir, S Nurmaini, B Tutuko - Big Data and Cognitive Computing, 2021 - mdpi.com
Text classification is an important component in many applications. Text classification has
attracted the attention of researchers to continue to develop innovations and build new …
attracted the attention of researchers to continue to develop innovations and build new …
Investigating the Dynamics of Social Media Addiction and Well-Being in Jordan: An Empirical Analysis
IHM Hatamleh, R Aissani - Social Sciences, 2024 - mdpi.com
This study examines the complex associations among social media usage, engagement,
addiction and subjective well-being. Employing a sophisticated framework that integrates …
addiction and subjective well-being. Employing a sophisticated framework that integrates …
Incremental hierarchical text clustering methods: a review
F Simeone, MO Chaves, A Esmin - arXiv preprint arXiv:2312.07769, 2023 - arxiv.org
The growth in Internet usage has contributed to a large volume of continuously available
data, and has created the need for automatic and efficient organization of the data. In this …
data, and has created the need for automatic and efficient organization of the data. In this …
[HTML][HTML] WhatsUp: An event resolution approach for co-occurring events in social media
The rapid growth of social media networks has resulted in the generation of a vast data
amount, making it impractical to conduct manual analyses to extract newsworthy events …
amount, making it impractical to conduct manual analyses to extract newsworthy events …
Text Classification of Cancer Clinical Trials Documents Using Deep Neural Network and Fine Grained Document Clustering
Clinical trials are any research studies involve human participation with health safety
outcomes. In clinical trials, there is the most important term called the eligibility criteria …
outcomes. In clinical trials, there is the most important term called the eligibility criteria …