The paper reports a study into recommendation algorithms and determination of their advantages and disadvantages. The method for developing recommendations based on collaborative filtering such as Content-Based Filtering (CBF), Collaborative Filtering (CF), and hybrid methods of Machine Learning (ML) has been improved. The paper describes the design principles and functional requirements to a recommendation system in the form of a Web application for choosing the content required by user using movies as an example. The research has focused on solving issues related to cold start and scalability within the method of collaborative filtering. To effectively address these tasks, we have used hybrid training methods. A hybrid recommendation system (HRS) has been practically implemented for providing relevant content recommendations using movies as an example, taking into consideration the user's personal preferences based on the constructed hybrid method. We have improved an algorithm for developing content recommendations based on the collaborative filtering and Machine Learning for the combined filtration of similarity indicators among users or goods. The hybrid algorithm receives initial information in a different form, normalizes it, and generates relevant recommendations based on a combination of CF and CBF methods. Machine Learning is capable of defining those factors that influence the selection of relevant films, which improves development of recommendations specific to the user. To solve these tasks, a new improved method has been proposed, underlying which, in contrast to existing systems of recommendations, are the hybrid methods and Machine Learning. Machine Learning data for the designed HRS were borrowed from MovieLens. We have analyzed methods for developing recommendations to the user; existing recommendation systems have been reviewed. Our experimental results demonstrate that the operational indicators for the proposed HRS, based on the technology of CF+CBF+ML, outperform those for two individual models, CF and CBF, and such their combinations as CF CBF, CF+ML, and CBF+ML. We recommend using HRS to collect data on people's preferences in selecting goods and to providing relevant recommendations.

/pdf/design-of-a-recommendation-system-based-on-collaborative-xs0j5333hz.pdf

Design of a recommendation system based on collaborative filtering and machine learning considering personal needs of the user

In this paper a controller construction on the basis of the intelligent agent with fuzzy logic is considered. The algorithm of a fuzzy logic inference of the agent decision-making is described. Results of computer modelling of control process are received and analysed.

The control agent with fuzzy logic

The aim of the work is to simplify the process of finding and planning travels for users through the use of the intellectual system of integration and content creation. Information sources that comprehensively describe the concept of tourist information resources are considered. An overview and comparison of certain indicators of existing tourism information and service provider services that can be considered conceptually identical to the system being developed are carried out. The existing data integration technologies were identified and analyzed, their advantages and disadvantages were examined, and the feasibility of using each of the technologies in the developed system is considered. The purpose of the system is analyzed, which is to simplify and speed up the travel planning process for the average user by providing him with all the necessary information. The boundaries of the system and the external environment in which it will function are identified; the components of the system, the main business processes, and data streams have been analyzed. A conceptual model of the system was created with the help of object notation. The list of requirements for the system, its input and output data, as well as the form of their display and dynamic characteristics are described. This work describes and analyzes the methods of data integration and content creation. The means of solving the problem were analyzed and the optimal means for the realization of the intellectual system of the formation and integration of the content is chosen taking into account the needs of the user. To implement the database, the MongoDB DBMS is selected. This article describes the structure of the system, the logic of the functions created software and processes and the results of their implementation. It is confirmed the correctness of the functioning of this system and the compliance of the results of the task. To do this, the program has been tested and shown in the drawings of all stages of its work. With manual testing, the program proved to be convenient and easy to use.

Online Tourism System Development for Searching and Planning Trips with User’s Requirements

A web-based service for the automation of contextual advertising management in Google AdWords system are developed. An analysis of the Internet advertising market, the vector of its development and the latest user needs are solved. Literary sources for deepening the knowledge about contextual advertising is analyzed. A few competing systems are found and analyzed, their deficiencies and advantages are determined. Conceptual model of the providing recommendations informational system on advertising services through Advertising Services is constructed. The set of potential software solutions and methods for the implementation of this system are analyzed. Among the advantages and disadvantages of each one the optimal solutions for implementing the system are shown and their choice is grounded. A web-based service for automating contextual advertising is designed.

/pdf/heterogeneous-data-with-agreed-content-aggregation-system-21mtqeqb7n.pdf

Heterogeneous Data with Agreed Content Aggregation System Development.

AHP study methods of solving problems to use AHP comparing alternatives (TOPSIS) and supervised learning algorithm using linear regression are proposed. To meet the challenges these methods were chosen language PHP, its own established framework CollEntRes, additional tools that helped during the programming process to detect errors and correct them (Debug), popular modern framework to work with the client part Angular, relational control systems, databases MariaDB HeidiSQL and its client, the technology to work with the client part of the site HTML and CSS and additional tools such as Bootstrap and SCSS. As a result, within practical implementation of software tool has been developed whose main goal is an analysis of matrix distant for recruitment in IT sector. The software tool covers general information and requirements for software, described in detail basic functionality of the software analysis and test cases for all kinds of users is presented in the article.

The Intellectual System Development of Distant Competencies Analyzing for IT Recruitment

The methods and means of using ontologies within systems for the categorization of textual content were created. Also, a method for optimizing the definition of which rubrics best relate to a certain text content was developed. The intellectual system that will use the methods developed earlier, as well as other research results was implemented. The results will allow users to easily filter their text content. The system developed has an intuitive user interface.

/pdf/development-of-information-system-for-textual-content-y5gmyb6ghg.pdf

Development of Information System for Textual Content Categorizing Based on Ontology.

The methods and means of using ontologies within systems for the categorization of textual content were created. Also, a method for optimizing the definition of which rubrics best relate to a certain text content was developed. The intellectual system that will use the methods developed earlier, as well as other research results was implemented. The results will allow users to easily filter their text content. The system developed has intuitive user interface.

/pdf/textual-content-categorizing-technology-development-based-on-11n1595cur.pdf

Textual Content Categorizing Technology Development Based on Ontology.

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Development of Information System for Textual Content Categorizing Based on Ontology.

Textual Content Categorizing Technology Development Based on Ontology.