EXPERT SYSTEMS

In recent decades IT and computer systems have evolved rapidly in economic informatics field. The goal is to create user friendly information systems that respond promptly and accurately to requests. Informatics systems evolved into decision assisted systems, and such systems are converted, based on gained experience, in expert systems for creative problem solving that an organization is facing. Expert systems are aimed at rebuilding human reasoning on the expertise obtained from experts, stores knowledge, establishes links between knowledge, have the knowledge and ability to perform human intellectual activities. From the informatics development point of view, expert systems are based on the principle of the knowledge separation from the treating program. Expert systems simulate the human experts reasoning on knowledge available to them, multiply the knowledge and explain their own lines of reasoning.expert systems, artificial intelligence, knowledge, expertise

An intelligent decision support system for machine learning algorithms recommendation

Machine learning is a very central topic in Artificial Intelligence and even computer science in general. Nowadays, its use in Big Data problems is quite well known. However, while the big data, and machine learning problems in general, are quite varied and in needing of different kinds of solutions, there are as well many different methods in machine learning that can be used. In this work, we propose an application that might help deciding on which machine learning methods a user needs for a specified problem. The application is an Intelligent Decision Support System for Machine Learning Algorithm Recommendation for which we present the design, which is centered around the combined use of the Case-Based Reasoning and RuleBased Reasoning, for the recommending process, while also trying to make the system easy to use and manage. We present a prototype of such a system, and the implementation details of the two recommender algorithms. The preliminary testing of the prototype shows it to be a promising tool

CHANGING LEARNING ENVIRONMENT THROUGH TECHNOLOGY

Evolution of E-learning phenomenon exceeded all expectations in recent years.As a result of development of IT&C technologies and, on the other hand, due to support decision-makers at European level, the assimilation of virtual learning platforms in schools and universities hasbecome a normal phenomenon.The E-learning 2.0 concept seeks to revolutionize traditional learning methods and requires majorchanges in the perception of the educational process of teaching and learning.This article tries to create an overview of the main development directions and emphasizes the impactthat computer-assisted instruction technologies have on teaching and learning methods, with a directconnection to distance learning and blended learning concepts. Also, we have tried to open aperspective on the concept of e-Assessment and related technologiese-learning 2.0, computer based training, e-assessment, blended learning, distance learning

THE ROLE AND IMPLICATIONS OF THE EVENT BASED COMMUNICATION IN THE ELECTORAL CAMPAIGN

The electoral campaigns are considered to be among the most delicate challenges for a marketer due to the limited time available, the sensible margin for error, the high impact of each statement and the condensation of a quite large amount of resources in a 30 day period. While the ultimate goal for the campaign staff is to bring the global electoral package closer to the electorate and earn their votes most, of the time various competitors use disappointingly similar tactics that create confusion among the electorate. The campaign related events turned out to be one of the tactics that allows for a pin-point targeting of the electorate and a better control on the receivers of the message. This paper focuses on the types of events used that can be used in an electoral campaign reinforced with their particularities and effects registered in previous campaigns.electoral marketing, communication, events, targeting, global electoral pachage

Solutions for decision support in university management

The paper proposes an overview of decision support systems in order to define the role of a system to assist decision in university management. The authors present new technologies and the basic concepts of multidimensional data analysis using models of business processes within the universities. Based on information provided by scientific literature and on the authors’ experience, the study aims to define selection criteria in choosing a development environment for designing a support system dedicated to university management. The contributions consist in designing a data warehouse model and models of OLAP analysis to assist decision in university management.university management, decision support, multidimensional analysis, data warehouse, OLAP

FROM DOCUMENT MANAGEMENT TO KNOWLEDGE MANAGEMENT

Documents circulating in paper form are increasingly being substituted by itselectronic equivalent in the modern office today so that any stored document can be retrievedwhenever needed later on. The office worker is already burdened with information overload, soeffective and effcient retrieval facilities become an important factor affecting worker productivity. The key thrust of this article is to analyse the benefits and importance of interaction betweendocument management and knowledge management. Information stored in text-based documentsrepresents a valuable repository for both the individual worker and the enterprise as a whole and ithas to be tapped into as part of the knowledge generation process.document management, knowledge management, Information and communication technologies

UPB @ ACTI: Detecting Conspiracies using fine tuned Sentence Transformers

Conspiracy theories have become a prominent and concerning aspect of online discourse, posing challenges to information integrity and societal trust. As such, we address conspiracy theory detection as proposed by the ACTI @ EVALITA 2023 shared task. The combination of pre-trained sentence Transformer models and data augmentation techniques enabled us to secure first place in the final leaderboard of both sub-tasks. Our methodology attained F1 scores of 85.71% in the binary classification and 91.23% for the fine-grained conspiracy topic classification, surpassing other competing systems