Nowadays, graphs including bigraphs are mostly used in various real-world applications such as search engines and social networks. The bigraph or bipartite graph is a graph whose vertex set is split into two disjoint vertex sets such that there is no edge between the same vertex set. The bipartite graphs are colored using only two colors. This article checks if a given graph is bipartite or not and finds the color assignments of the bipartite graph using Java implementation.

Most people can't subscribe to every direct-to-consumer platform today, and the number is growing. The platform's content and the user's experience influence the decision to subscribe or buy. Today's consumers anticipate instantaneously curated content exploration, acquisition, and consumption. Media firms actively seek to increase both click-through rate and profitability by enhancing the user experience and enticing customers to subscribe or buy premium content through recommender systems. The direct-to-consumer platforms may maintain user engagement after consumers have visited the contents by providing suggestions that make the most of the site's rich content catalogs. By bringing it to the attention of viewers based on their viewing habits, for instance, effective recommendation systems might boost earnings for underappreciated "long tail" content. This research explores various recommender system types currently in widespread usage with an analysis of some of the fascinating breakthroughs.

There are different traditional and nontraditional datasets available to investigate the performance of recommender systems. This article focuses on the different datasets required for the investigation of recommender systems.

Electronics and computer engineering is a scientific and technical field in which electronic and computer systems are studied and their use. They are related to the technical professions within which electronic devices, systems, and computer programs are realized. The past half-century has been greatly marked by the development of electronics, computing, and their application in communications, medicine, and industry. This field has become the fundamental technical infrastructure of modern society. Today, there is almost no electronic device that does not use an electronic computer, and there is also not a single computer that is almost exclusively made of electronic components. This article explores the need for electronic components in digital computing.

One of the most important applications of data science is the recommendation system. Every organization requires a good recommendation system to express a large range of items. This research focuses on the creation of a book recommender system using collaborative filtering.

Everyone likes movies irrespective of color, gender, age, location, and race. The most important thing is how the users are getting our unique combinations of choices concerning the preferences of the movies. This article focuses on the creation of a movie recommendation system using item-based collaborative filtering.

Graph coloring, an NP-complete problem is used in many real-world applications. The minimum color, that is, the chromatic number of a connected graph is determined using different soft computing strategies. This article gives some of the solutions obtained for queen graphs using evolutionary methods.

Recently recommender systems are developed for a wide variety of applications. This article focuses on the applications, real-world examples, types, and analysis of various recommender systems.

The task of recommending products to customers based on their interests is important in business. It is possible to accomplish this with machine learning. To reduce human effort by proposing movies based on the user's interests efficiently and effectively without wasting much time in pointless browsing, the movie recommendation system is designed to assist movie aficionados. This work focuses on developing a movie recommender system using a model that incorporates both cosine similarity and sentiment analysis. Cosine similarity is a standard used to determine how similar two items are to one another. An examination of the emotions expressed in a movie review can determine how excellent or negative a review is and, consequently the overall rating for a film. As a result, determining whether a review is favorable or adverse may be automated because the machine learns by training and evaluating the data. Comparing different systems based on content-based approaches will produce results that are increasingly explicit as time passes.

An algorithm is defined as a finite step-by-step procedure to accomplish a required result. It is also defined as a sequence of computational operations that convert the given input into the required output. In general, in the worst case, an algorithm is said to be optimal if there are no algorithms that perform a less basic number of well-defined operations, in the worst case. This paper presents an optimal algorithm for finding the second smallest among n numbers. The complexity of the proposed algorithm and its advantages are also analyzed in this paper.

Nowadays, recommendation systems are existing everywhere in the internet world, online people are presented with the required needs not just for actual physical products, but also for several other things such as songs, places, books, friends, movies, and many more requirements. Most of the systems are developed with the basic collaborative and hybrid filtering, where the people or users are recommended items that the choices are based on the right preferences of other people by applying the machine intelligence strategies. In this research, the importance of network modeling is analyzed in solving real-world problems.