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[HTML][HTML] World on data perspective
It is not simple to consider the world from only one side, but analyzing all sides can cloud
comprehension without reaching deep insight found at the core. In a word as a whole, there …
comprehension without reaching deep insight found at the core. In a word as a whole, there …
Connections between various disorders: combination pattern mining using apriori algorithm based on diagnosis information from electronic medical records
H Ma, J Ding, M Liu, Y Liu - BioMed Research International, 2022 - Wiley Online Library
Objective. Short‐term or long‐term connections between different diseases have not been
fully acknowledged. This study was aimed at exploring the network association pattern …
fully acknowledged. This study was aimed at exploring the network association pattern …
Toward a cognitive-inspired hashtag recommendation for twitter data analysis
This research investigates hashtag suggestions in a heterogeneous and huge social
network, as well as a cognitive-based deep learning solution based on distributed …
network, as well as a cognitive-based deep learning solution based on distributed …
Managing and Retrieving Bilingual Documents Using Artificial Intelligence‐Based Ontological Framework
In recent times, artificial intelligence (AI) methods have been applied in document and
content management to make decisions and improve the organization's functionalities …
content management to make decisions and improve the organization's functionalities …
A federated convolution transformer for fake news detection
We present a novel approach to detect fake news in Internet of Things (IoT) applications. By
investigating federated learning and trusted authority methods, we address the issue of data …
investigating federated learning and trusted authority methods, we address the issue of data …
[PDF][PDF] Addressing limitations of the K-means clustering algorithm: Outliers, non-spherical data, and optimal cluster selection
Addressing limitations of the K-means clustering algorithm: outliers, non-spherical data, and
optimal cluster selection Page 1 AIMS Mathematics, 9(9): 25070–25097. DOI: 10.3934/math.20241222 …
optimal cluster selection Page 1 AIMS Mathematics, 9(9): 25070–25097. DOI: 10.3934/math.20241222 …
Comparative Analysis of Optimization Strategies for K-means Clustering in Big Data Contexts: A Review
This paper presents a comparative analysis of different optimization techniques for the K-
means algorithm in the context of big data. K-means is a widely used clustering algorithm …
means algorithm in the context of big data. K-means is a widely used clustering algorithm …
[PDF][PDF] Fully Automated Density-Based Clustering Method.
Cluster analysis is a crucial technique in unsupervised machine learning, pattern
recognition, and data analysis. However, current clustering algorithms suffer from the need …
recognition, and data analysis. However, current clustering algorithms suffer from the need …
Short text matching model with multiway semantic interaction based on multi-granularity semantic embedding
Short text matching is a fundamental technique of natural language processing. It plays an
important role in information retrieval, question answering and paraphrase identification, etc …
important role in information retrieval, question answering and paraphrase identification, etc …
A semantics-based clustering approach for online laboratories using K-Means and HAC algorithms
Due to the availability of a vast amount of unstructured data in various forms (eg, the web,
social networks, etc.), the clustering of text documents has become increasingly important …
social networks, etc.), the clustering of text documents has become increasingly important …