Anisotropic Bianchi type-III model in Palatini f ( R ) $f (R)$ gravity

Banik, Debika Kangsha; Banik, S.; Bhuyan, Kalyan

doi:10.1007/s10509-017-3031-1

Cited by 11 publications

(3 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…While the N j stands for the number of samples in C j (k), if a j (k + 1) = a j (k) for j = 1, 2, 3, ...K, then the algorithm become halt due to converged action, otherwise repeat second step (5).…”

Section: K-means Clusteringmentioning

confidence: 99%

See 1 more Smart Citation

Natural Language Processing-based Method for Clustering and Analysis of Movie Reviews and Classification by Genre

González,

Torres-Ruiz,

Rivera-Torruco

et al. 2023

Preprint

View full text Add to dashboard Cite

The large quantity of information retrieved from communities, public data repositories, web pages, or data mining can be sparsed and poorly classified. This work shows how to employ unsupervised classification algorithms such as K-means proper to classify user reviews into their closest category, forming a balanced data set. Moreover, we found that the text vectorization technique significantly impacts the clustering formation, comparing TF-IDF and Word2Vec. The value for mapping a cluster with movie genre was 81.34% ± 20.48 of the cases when the TF-IDF was applied, whereas Word2Vec only yielded a 53.51% ± 24.1. In addition, we highlight the impact of the removal of stop-words. Thus, we detected that pre-compiled lists are not the best method to remove stop-words before clustering because there is much ambiguity, centroids are poorly separated, and only 57% of clusters could match a movie genre. Thus, our proposed approach achieved a 94% of accuracy. After analyzing the classifiers’ results, we appreciated a similar effect when divided by the stop-words method removal. Statistically significant changes were observed, especially in precision metric and Jaccard scores in both classifiers, using custom-generated stop lists rather than pre-compiled ones. Reclassifying sparse data is strongly recommended as using custom-generated stop lists.

show abstract

Section: K-means Clusteringmentioning

confidence: 99%

“…Other popular datasets are "The movie dataset" by Rounak Banik [5], containing principally rating and metadata but no text data information, and "IMDb Dataset of 50K Movie Reviews" by Lakshmi Pathi [6] being composed of movie metadata and reviews from 50,000 movies.…”

Section: Introductionmentioning

confidence: 99%

Natural Language Processing-based Method for Clustering and Analysis of Movie Reviews and Classification by Genre

González,

Torres-Ruiz,

Rivera-Torruco

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…This provides a strong motivation to look for some alternative models to explain such anisotropy. Bianchi models [39][40][41][42][43][44][45][46][47][48][49][50][51][52][53] pave a way for the researchers to describe the anisotropic phase of early universe and the acceleration phase of late universe.…”

Section: Introductionmentioning

confidence: 99%

Bianchi I and V cosmologies with Hu-Sawicki f(R) gravity in Palatini formalism

Banik

Bhuyan

2018

J. Phys. Commun.

Self Cite

View full text Add to dashboard Cite

The main objective of this work is the pursuit of a detailed analysis of the cosmological solutions corresponding to each fixed point belonging to an exclusive form of f (R) initially introduced by Hu and Sawicki in the background of Palatini f (R) gravity. Fixed points and their associated solutions for the anisotropic Bianchi type I and V models are derived by utilizing an approach used to solve autonomous ordinary differential equations. Building on this background, an exhaustive study on the phase space is accomplished and the existence of a sequence of evolution that starts from unstable anisotropic universe to a stable phase of late times de Sitter expansion through the standard radiation and matter dominated era has been established.

show abstract

Bianchi III Cosmologies for the Form $$f(R)=R-\beta /R^n$$ Using the Palatini Formalism

Banik

Bhuyan

2018

XXII DAE High Energy Physics Symposium

View full text Add to dashboard Cite

Anisotropic Bianchi type-III model in Palatini f ( R ) $f (R)$ gravity

Cited by 11 publications

References 36 publications

Natural Language Processing-based Method for Clustering and Analysis of Movie Reviews and Classification by Genre

Natural Language Processing-based Method for Clustering and Analysis of Movie Reviews and Classification by Genre

Bianchi I and V cosmologies with Hu-Sawicki f(R) gravity in Palatini formalism

Bianchi III Cosmologies for the Form $$f(R)=R-\beta /R^n$$ Using the Palatini Formalism

Contact Info

Product

Resources

About