English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Text classification is playing a vital role in current era. Its requirement is increasing day by day because of increase of text data as number of digital users are increasing rapidly. As a result, machine learning algorithms are used to classify certain text data, resulting in better predictions and accuracy. By constructing a data set with proper structure and data, the genre is predicted by the title and abstract of the book. The dataset will consist books which are translated to English from Guajarati or Hindi originate books. In this paper, some weaknesses in text classification techniques are analysed and worked on to improve the accuracy of structured data. The main focus here was to classify a book by genre using machine learning algorithms. Keywords— Text Classification, Book Categorization, K-Nearest Neighbor (K-NN), Support Vector Machine (SVM), Logistic Regression (LR), Text Mining, Machine Learning, Genre Prediction.

international journal of computer science and mobile computing

Book Genre Categorization Using Machine Learning Algorithms (K-Nearest Neighbor, Support Vector Machine and Logistic Regression) using Customized Dataset﻿

Book Genre Categorization Using Machine Learning Algorithms (K-Nearest Neighbor, Support Vector Machine and Logistic Regression) using Customized Dataset﻿

Book Genre Categorization Using Machine Learning Algorithms (K-Nearest Neighbor, Support Vector Machine and Logistic Regression) using Customized Dataset