Expert system with Fuzzy logic for protecting Scientific Information Resources

Rakhmatullaev, Marat; Normatov, Sherbek

doi:10.1109/aict50176.2020.9368598

Cited by 3 publications

(3 citation statements)

References 5 publications

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“…Our study findings indicate that RSs have found widespread application within digital libraries, and the research in RS has contributed to the evolution of effective information retrieval systems for UDL by providing personalized recommendations and ease of accessibility for users. This is evident from the research by Rakhmatullaev et al, (2023) which emphasizes the need for recommendation techniques for information retrieval systems to provide relevant information at the right time to the library users as per their needs and preferences. 2) The results of our study suggest the development of RS has led to advancements in user modeling techniques like collaborative filtering, content-based, and hybrid approaches based on natural language processing, semantics, and ontology to cater to users' varied linguistic preferences and tailored to their behaviors.…”

Section: Discussionmentioning

confidence: 99%

Mapping the research landscape of recommender systems for digital libraries

Awal,

Tehlan

2024

RLJ

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Background of the study: In today’s information-rich environment, researchers face the difficulty of managing information overload and struggle to identify meaningful information among a plethora of choices. A recommender system plays a crucial role in assisting users in discovering relevant information from a digital library. Purpose: This study aims to provide a bibliometric analysis of research publications on recommender systems for digital libraries. Method: The research method involved the quantitative bibliometric approach to analyse the research publications from the Web of Science and Scopus databases using Biblioshiny. The dataset retrieved comprises 374 documents published between the period of 2004-2023. Findings: The study's findings highlight that the number of publications was notably high in 2009 and 2018 within the analyzed period. The most significant contributors are Porcel C, Herrera-Viedma E, and Beel J. There is a considerable international collaboration between the countries- China, USA, and Germany. Conclusions: This study indicates an emerging interest in recommender systems for digital libraries with the continuous evolution of new recommendation models. There is a huge potential for research considering the availability of multimodal data, the continuous evolution of new technologies such as deep learning, and opportunities for the development of an architecture for integrating different digital libraries.

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Section: Discussionmentioning

confidence: 99%

Mapping the research landscape of recommender systems for digital libraries

Awal,

Tehlan

2024

RLJ

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“…Students' knowledge is the main feature that determines the appropriate teaching system, and it is important to support them in the subject being taught, give appropriate instructions and adapt the lesson content. Today, some organizational systems take into account the knowledge and skills possessed by users and determine whether a suitable vacancy is available [2,5].…”

Section: Knowledge and Skillsmentioning

confidence: 99%

“…For example, recommendation-oriented information systems capture the characteristics of registered users, find similar users based on input data, and offer personalized information and services that ultimately satisfy users' information needs. There are two main approaches to user modeling [5,12]:…”

Section: Introductionmentioning

confidence: 99%

Extended User Profiling Approaches for Recommendation Systems

Bekkamov,

Sharifov

2024

ETR

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Currently, the volume of data in information systems and the information needs of users are increasing. This causes information overload and a number of difficulties in finding the necessary information. Therefore, individual approaches, including personalization of user profiles, are important in solving this problem. Creating a user profile is relevant for obtaining information from systems in accordance with the needs of the user and for personalizing the services provided by the system. The lack of direct user profiling in information systems creates a number of problems in providing personalized services to users. Around the world, recent research has focused on developing systems that personalize user profiles based on their data sets. The work done so far on a global scale to create and model user profiles is analyzed. In this article, mathematical algorithms such as TF-IDF, Cosine similarity, Word2Vec are used to model and personalize user data. It also provides a classification scheme for user profiling, modeling and personalization. This classification scheme is based on three components. These are user data collection, user profiling, modeling and personalization components. Additionally, the article also mentions the benefits of user identification.

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The information library infrastructure of Uzbekistan: The three-level management model

Rakhmatullaev

2022

Naučnye i tehničeskie biblioteki

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The current trends in information infrastructure and its component information library infrastructure (ILI) are analyzed. The specific characteristics of Uzbekistan ILI are: building libraries for modern technological applications and developing existing infrastructure. The main problems the ministries and library community face are revealed. The ILI organizational model based on hierarchy is discussed. The author considers the three-level system to be the most efficient for the libraries' interdepartmental interaction. This would provide for information cooperation in building union resources (e-catalogs, databases), and library management. Taking into account the specific character of library management in the Republic of Uzbekistan, the ILI based on the corporate library networks of various departments would enable: to computerize information acquisition, accumulation and transfer at all levels for efficient management; to provide open access to union e-catalog for all libraries and users; to build libraries' local digital resources; to increase efficiency of interaction and cooperation between the National Library and the libraries of various departments; to save money and human assets through excluded work duplication and intensive information exchange.

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Expert system with Fuzzy logic for protecting Scientific Information Resources

Cited by 3 publications

References 5 publications

Mapping the research landscape of recommender systems for digital libraries

Mapping the research landscape of recommender systems for digital libraries

Extended User Profiling Approaches for Recommendation Systems

The information library infrastructure of Uzbekistan: The three-level management model

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