Hybrid categorical expert system for the use in content aggregation

@article{Kiryanov2021HybridCE,
  title={Hybrid categorical expert system for the use in content aggregation},
  author={Denis Aleksandrovich Kiryanov},
  journal={Программные системы и вычислительные методы},
  year={2021}
}
  • Denis Aleksandrovich Kiryanov
  • Published 1 April 2021
  • Computer Science
  • Программные системы и вычислительные методы
The subject of this research is the development of the architecture of expert system for distributed content aggregation system, the main purpose of which is the categorization of aggregated data. The author examines the advantages and disadvantages of expert systems, toolset for development of expert systems, classification of expert systems, as well as application of expert systems for categorization of data. Special attention is given to the description of architecture of the proposed… 
2 Citations

Research of the methods of creating content aggregation systems

Recommendations are given on the selection of the architecture of styles and special software regime that allows creating the systems for managing distributed databases and message brokers, and the presented architecture aims to provide high availability, scalability for high query volumes, and big data performance.

A Scalable Aggregation System Designed to Process 50,000 RSS Feeds

The main conclusion of the study is that before developing an aggregation system, it is necessary to analyze the publication activity of data sources, on the basis of which it is possible to form an acceptable strategy for updating the search index, saving a significant amount of resources.

References

SHOWING 1-10 OF 56 REFERENCES

Designing an AI Expert System

The project became more than just a design and development of a single application, it became a means to learn and understand expert systems technology as a category of artificial intelligence.

Rule Based Systems for Big Data

A unified framework for building rule based systems, which consists of the operations of rule generation, rule simplification and rule representation, is presented and each of these operations is detailed using specific methods or techniques.

The GENIE Project - A Semantic Pipeline for Automatic Document Categorisation

A multi-language rule-based pipeline system for automatic document categorisation is proposed and the results of applying techniques that rely on statistics and supervised learning with the support of smarter tools based on language semantics and ontologies are compared.

Developing a Prototype Knowledge-Based System for Diagnosis and Treatment of Diabetes Using Data Mining Techniques

The J48 model was the best performing model with the best accuracy of results, and the second most performing model was generated by JRip Classier.

Prototyping Rule-Based Expert Systems with the Aid of Model Transformations

The paper presents a detailed description of the main elements of the approach including models, transformations and a specialised software (Personal Knowledge Base Designer) that makes the design process of rule-based expert systems and knowledge bases more efficient.

Feature Extraction with TF-IDF and Game-Theoretic Shadowed Sets

Game-theoretic shadowed sets determine the thresholds of TF-IDF using game theory and repetition learning mechanism and experimental results show that this model not only outperforms all baseline cut-off approaches, but also speeds up the classification algorithms.

Rule-Based Expert Systems

Rule-based systems are the simplest form of artificial intelligence that represents knowledge in terms of a set of rules that tells what to do or what to conclude in different situations.

Expert System For Diagnosis Pest And Disease In Fruit Plants

This paper discussed the development of an expert system to diagnose pests and diseases on fruit plants. Rule base method was used to store the knowledge from experts and literatures. Control
...