• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.71-78
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• 2021

The relevance of research provides the necessity to identify the basic problems in the public governance sphere and information technology relations, forasmuch as understanding such interconnections can indicate the consequences of the development and spreading information technologies. The purpose of the research is to outline the issues of applying information technologies in public governance sphere. 500 civil servants took part in the survey (Ukraine). A two-stage study was conducted in order to obtain practical results of the research. The first stage involved collecting and analyzing the responses of civil servants on the Mentimeter online platform. In the second stage, the administrator used the SWOT-analysis system. The tendencies in using information technologies have been determined as follows: the institutional support development; creation of analytical portals for ensuring public control; level of accountability, transparency, activity of civil servants; implementation of e-government projects; changing the philosophy of electronic services development. Considering the threats and risks to the public governance system in the context of applying information technologies, the following aspects generated by societal requirements have been identified, namely: creation of the digital bureaucracy system; preservation of information and digital inequality; insufficient level of knowledge and skills in the field of digital technologies, reducing the publicity of the state and municipal governance system. Weaknesses of modern public governance in the context of IT implementation have been highlighted, namely: "digitization for digitalization"; lack of necessary legal regulation; inefficiency of electronic document management (issues caused by the imperfection of the interface of reporting interactive forms, frequent changes in the composition of indicators in reporting forms, the desire of higher authorities to solve the problem of their introduction); lack of data analysis infrastructure (due to imperfections in the organization of interaction between departments and poor capacity of information resources; lack of analytical databases), lack of necessary digital competencies for civil servants. Based on the results of SWOT-analysis, the strengths have been identified as follows: (possibility of continuous communication; constant self-learning); weaknesses (age restrictions for civil servants; insufficient acquisition of knowledge); threats (system errors in the provision of services through automation); opportunities for the introduction of IT in the public governance system (broad global trends; facilitation of the document management system). The practical significance of the research lies in providing recommendations for eliminating the problems of IT implementation in the public governance sphere outlined by civil servants..

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.129-164
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• 2023

In a situation where the use and introduction of Large Language Models (LLMs) is expanding due to recent developments in generative AI technology, it is difficult to find actual application cases or implementation methods for the use of internal company data in existing studies. Accordingly, this study presents a method of implementing generative AI services using the LLM application architecture using the most widely used LangChain framework. To this end, we reviewed various ways to overcome the problem of lack of information, focusing on the use of LLM, and presented specific solutions. To this end, we analyze methods of fine-tuning or direct use of document information and look in detail at the main steps of information storage and retrieval methods using the retrieval augmented generation (RAG) model to solve these problems. In particular, similar context recommendation and Question-Answering (QA) systems were utilized as a method to store and search information in a vector store using the RAG model. In addition, the specific operation method, major implementation steps and cases, including implementation source and user interface were presented to enhance understanding of generative AI technology. This has meaning and value in enabling LLM to be actively utilized in implementing services within companies.

• The Journal of Information Technology
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• v.4 no.1
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• pp.125-139
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• 2001

EDI(Electronic Data Interchange) works by providing a collection of standard message formats and element dictionary in a simple way for businesses to exchange data via any electronic messaging service. Open-edi is electronic data interchange among autonomous parties using public standards and aiming towards interoperability over time, business sectors, information technology and data types. The number of Internet services using XML/EDI has grown rapidly since it is easily expansible and exchangeable. To use this service, the client does not have to install EDI S/W but only needs internet browser. Consequently, it became much easier and faster to handle the trading process in an office. eBusiness SML (extensible markup language) electronic data interchange. eXedi is the service that realizes B2B of XML/EDI. eXedi can be used easily in small and medium sized companies. Companies in any place can access to eXedi using the existing Internet connection. XML/EDI provides a standard framework to exchange different types of data -- for example, an invoice, healthcare claim, project status -- so that the information be it in a transaction, exchanged via an Application Program Interface (API), web automation, database portal, catalog, a workflow document or message can be searched, decoded, manipulated, and displayed consistently and correctly by first implementing EDI dictionaries and extending our vocabulary via on-line repositories to include our business language, rules and objects.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.121-125
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• 2007

This paper proposes automatic generation method of proxy client code to automation of web service selection process through a monitoring agent. The technique of this paper help service consumer to provide source code of proxy client as it bring an attribute value of specific element of WSDL document using template rule. Namely, a XSLT script file provide code frame of dynamic invocation interface model. The automatic code generation technique need to solving starvation status of selection architecture. It is required to creating request HTTP message for every service on the result of search. The created proxy client program code generate dummy message about services. The proposed client code generation method show us a possibility of application in the automatic generation programming domain.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.228-235
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• 2008

This paper proposes automatic generation method of proxy client code to automation of web service selection process through a monitoring agent. The technique of this paper help service consumer to provide source code of proxy client as it bring an attribute value of specific element of WSDL document using template rule. Namely, a XSLT script file provide code frame of dynamic invocation interface model. The automatic code generation technique need to solving starvation status of selection architecture. It is required to creating request HTTP message for every service on the result of search. The created proxy client program code generate dummy message about services. The proposed client code generation method show us a possibility of application in the automatic generation programming domain.

• The KIPS Transactions:PartA
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• v.12A no.6 s.96
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• pp.485-492
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• 2005

Currently workflows in business processes and distributed computing environments have provided service automation by connecting many tasks with rules and/or orderings. The services in ubiquitous computing environments have to automatically provide users with adaptive services according to dynamically changing contort information, which is obtained from both the users and their environment. To adapt these workflows to ubiquitous computing, we must specify the situation information on the transition conditions. In this paper, we propose uWDL, Ubiquitous Workflow Description Language, based on Web Services to use the situation information on the transition constraints of workflow's services. uWDL can select adaptive services according to contexts, profiles, and events information, which are situation information. Furthermore, we verified the execution of a scenario document described with uWDL using the parser and the context handler for uWDL. The scenario developers can use the uWDL scenario editor for a design of scenarios, and they can easily specify the transition condition of the services according the situation information of ubiquitous environments using the uWDL.

• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.108-117
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• 2024

The selection and recommendation of a suitable job applicant from the pool of thousands of applications are often daunting jobs for an employer. The recommendation and selection process significantly increases the workload of the concerned department of an employer. Thus, Resume Classification System using the Natural Language Processing (NLP) and Machine Learning (ML) techniques could automate this tedious process and ease the job of an employer. Moreover, the automation of this process can significantly expedite and transparent the applicants' selection process with mere human involvement. Nevertheless, various Machine Learning approaches have been proposed to develop Resume Classification Systems. However, this study presents an automated NLP and ML-based system that classifies the Resumes according to job categories with performance guarantees. This study employs various ML algorithms and NLP techniques to measure the accuracy of Resume Classification Systems and proposes a solution with better accuracy and reliability in different settings. To demonstrate the significance of NLP & ML techniques for processing & classification of Resumes, the extracted features were tested on nine machine learning models Support Vector Machine - SVM (Linear, SGD, SVC & NuSVC), Naïve Bayes (Bernoulli, Multinomial & Gaussian), K-Nearest Neighbor (KNN) and Logistic Regression (LR). The Term-Frequency Inverse Document (TF-IDF) feature representation scheme proven suitable for Resume Classification Task. The developed models were evaluated using F-Score_M, Recall_M, Precission_M, and overall Accuracy. The experimental results indicate that using the One-Vs-Rest-Classification strategy for this multi-class Resume Classification task, the SVM class of Machine Learning algorithms performed better on the study dataset with over 96% overall accuracy. The promising results suggest that NLP & ML techniques employed in this study could be used for the Resume Classification task.

• Journal of KIISE
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• v.44 no.2
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• pp.139-147
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• 2017

Most of the information prevailing in the Internet space consists of textual information. So one of the main topics regarding the huge document analyses that are required in the "big data" era is the development of an automated understanding system for textual data; accordingly, the automation of the keyword extraction for text summarization and abstraction is a typical research problem. But the simple listing of a few keywords is insufficient to reveal the complex semantic structures of the general texts. In this paper, a text-visualization method that constructs a graph by computing the related degrees from the selected keywords of the target text is developed; therefore, two construction models that provide the edge relation are proposed for the computing of the relation degree among keywords, as follows: influence-interval model and word- distance model. The finally visualized graph from the keyword-derived edge relation is more flexible and useful for the display of the meaning structure of the target text; furthermore, this abstract graph enables a fast and easy understanding of the target text. The authors' experiment showed that the proposed abstract-graph model is superior to the keyword list for the attainment of a semantic and comparitive understanding of text.