Correspondence analysis-based network clustering and importance of degenerate solutions unification of spectral clustering and modularity maximization

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Masaomi Kimura
Keyword(s):  
Correspondence Analysis ◽  
Spectral Clustering ◽  
Network Clustering ◽  
Modularity Maximization ◽  
Degenerate Solutions

scholarly journals Correspondence analysis, spectral clustering and graph embedding: applications to ecology and economic complexity

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Alje van Dam ◽  
Mark Dekker ◽  
Ignacio Morales-Castilla ◽  
Miguel Á. Rodríguez ◽  
David Wichmann ◽  
...  
Keyword(s):  
Correspondence Analysis ◽  
Spectral Clustering ◽  
Classical Method ◽  
High Dimensional Data ◽  
Graph Embedding ◽  
Global Distribution ◽  
High Dimensional ◽  
Empirical Results ◽  
Economic Complexity ◽  
Scientific Disciplines

AbstractIdentifying structure underlying high-dimensional data is a common challenge across scientific disciplines. We revisit correspondence analysis (CA), a classical method revealing such structures, from a network perspective. We present the poorly-known equivalence of CA to spectral clustering and graph-embedding techniques. We point out a number of complementary interpretations of CA results, other than its traditional interpretation as an ordination technique. These interpretations relate to the structure of the underlying networks. We then discuss an empirical example drawn from ecology, where we apply CA to the global distribution of Carnivora species to show how both the clustering and ordination interpretation can be used to find gradients in clustered data. In the second empirical example, we revisit the economic complexity index as an application of correspondence analysis, and use the different interpretations of the method to shed new light on the empirical results within this literature.

Analysis on Research Paper Publication Recommendation System with Composition of Papers and Conferences Matrices

2020 ◽  
pp. 120-127
Author(s):  
Htay Htay Win ◽  
Aye Thida Myint ◽  
Mi Cho Cho
Keyword(s):  
Social Network ◽  
Dimensionality Reduction ◽  
Correspondence Analysis ◽  
Recommendation System ◽  
Research Paper ◽  
Topic Modelling ◽  
Research Papers ◽  
The Right ◽  
Publication Recommendation

For years, achievements and discoveries made by researcher are made aware through research papers published in appropriate journals or conferences. Many a time, established s researcher and mainly new user are caught up in the predicament of choosing an appropriate conference to get their work all the time. Every scienti?c conference and journal is inclined towards a particular ?eld of research and there is a extensive group of them for any particular ?eld. Choosing an appropriate venue is needed as it helps in reaching out to the right listener and also to further one’s chance of getting their paper published. In this work, we address the problem of recommending appropriate conferences to the authors to increase their chances of receipt. We present three di?erent approaches for the same involving the use of social network of the authors and the content of the paper in the settings of dimensionality reduction and topic modelling. In all these approaches, we apply Correspondence Analysis (CA) to obtain appropriate relationships between the entities in question, such as conferences and papers. Our models show hopeful results when compared with existing methods such as content-based ?ltering, collaborative ?ltering and hybrid ?ltering.

Contribution a la rationalisation du reseau qualite de l’eau de la Baie James

1977 ◽  
Vol 12 (1) ◽  
pp. 51-76
Author(s):  
B. Bobée ◽  
D. Cluis ◽  
A. Tessier
Keyword(s):  
Correspondence Analysis ◽  
Major Ions ◽  
Base Station ◽  
Base Stations ◽  
James Bay ◽  
Mean Values ◽  
Multivariate Technique ◽  
Qualité De L’Eau ◽  
Concentration Changes ◽  
The Relationship

Abstract A water quality sampling programme for James Bay territory established in a previous study has been carried out for the Department of Natural Resources of the Province of Quebec. The network is composed of 5 base-stations, sampled every fortnight to determine the variability with time of the parameters and 16 satellite-stations, sampled five times yearly with a view to determine the spatial variability. The data (major ions and certain nutrients) gathered during the 1974–1975 field survey are subjected to an analysis by a multivariate technique (correspondence analysis) in addition to certain classical statistical methods. The latter have shown that the mean values obtained at satellite stations were representative of the annual mean. In addition, the results permit the determination for a given parameter, of the relationship between stations and, for a given station, the relationship between parameters. In both cases, the formulation of predictive equations was attempted. An overall evaluation of the data by correspondence analysis has permitted: - a more precise definition of the qualitative behaviour of the different sub-basins of the James Bay territory and characterization of their waters;- a proof of the existence of gradual concentration changes in both East-West and North-South directions. Within the original objectives of the network, the results of the study have led to the following recommendations: - to continue synchronised samplings;- to transform a base station with a low information content into a satellite station;- to create a new base station in the eastern part of the territory.

Biomarker Identification for Liver Hepatocellular Carcinoma and Cholangiocarcinoma Based on Gene Regulatory Network Analysis

2020 ◽  
Vol 15 ◽  
Author(s):  
Qiuyan Huo ◽  
Yuying Ma ◽  
Yu Yin ◽  
Guimin Qin
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regulatory Networks ◽  
Primary Liver Cancer ◽  
Endocrine Resistance ◽  
Molecular Characteristics ◽  
Network Clustering ◽  
Resistance Pathway ◽  
Gene Regulatory ◽  
Tf Gene ◽  
Liver Hepatocellular Carcinoma

Aims: We aimed to find common and distinct molecular characteristics between LIHC and CHOL based on miRNA-TF-gene FFL. Background: Liver hepatocellular carcinoma (LIHC) and cholangiocarcinoma (CHOL) are two main histological subtypes of primary liver cancer with a unified molecular landscape, and feed-forward loops (FFLs) have been shown to be relevant in these complex diseases. Objective: To date, there has been no comparative analysis of the pathogenesis of LIHC and CHOL based on regulatory relationships. Therefore, we investigated the common and distinct regulatory properties of LIHC and CHOL in terms of gene regulatory networks. Method: Based on identified FFLs and an analysis of pathway enrichment, we constructed pathway-specific co-expression networks and further predicted biomarkers for these cancers by network clustering. Resul: We identified 20 and 36 candidate genes for LIHC and CHOL, respectively. The literature from PubMed supports the reliability of our results. Conclusion: Our results indicated that the hsa01522-Endocrine resistance pathway was associated with both LIHC and CHOL. Additionally, six genes (SPARC, CTHRC1, COL4A1, EDIL3, LAMA4 and OLFML2B) were predicted to be highly associated with both cancers, of which SPARC was significantly highly ranked. Other: In addition, we inferred that the Collagen gene family, which appeared more frequently in our overall prediction results, might be closely related to cancer development.

A Method for Multi-HVDC Grouping Based on Spectral Clustering

2020 ◽  
Author(s):  
Xiaohui Wang ◽  
Yu Bai ◽  
Yadong Gao ◽  
Dong Liu ◽  
Yan Zhang ◽  
...  
Keyword(s):  
Spectral Clustering
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