Intelligent University Library Information Systems to Support Students Efficient Learning

Iantovics, László Barna; Rotar, Corina; Nechita, Elena

doi:10.1007/978-3-030-04224-0_17

Cited by 2 publications

(2 citation statements)

References 21 publications

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“…To obtain the optimal solution to the original problem, the feasible solution of the dual problem needs to satisfy the Karuch-Kuhn-Tucker (KKT) conditions. That is, solving the minimum of the Lagrangian function L relative to φ, c, and γ: The results of formula (18) were simplified and substituted into formula (17). Then, the dual problem can be obtained by maximizing τ value:…”

Section: Figure 4 the Formal Description Model Of Landi Resourcesmentioning

confidence: 99%

“…In addition, there is a lack of direct channels between multi-source L&I resource platforms. It is time-consuming to browse and acquire knowledge on multiple platforms [15][16][17]. Many scholars have explored the ways to aggregate the knowledge in L&I resources, aiming to scientifically organize, mine, and manage the knowledge, and to innovate the knowledge service model [18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

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Resource Classification and Knowledge Aggregation of Library and Information Based on Data Mining

Qin¹

2020

ISI

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The traditional knowledge service systems have nonuniform data structures. Some data are structured, while some are semi-structured and even non-structured. Big data technology helps to optimize the integration and retrieval of the massive data on library and information (L&I), making it possible to classify the resources and optimize the configuration of L&I resource platforms according to user demand. Therefore, this paper introduces the new information service model of big data resources and knowledge services to the processing of L&I data. Firstly, the data storage structure and relationship model of the L&I resource platform were established, and used to sample and integrate the keywords of resource retrieval. Next, an L&I resource classification model was constructed based on support vector machine (SVM), and applied to extract and quantify the attributes of the keywords of resource retrieval. After that, a knowledge aggregation model was developed for a complex network of multiple L&I resource platforms. Experimental results demonstrate the effectiveness of the proposed knowledge aggregation model. The research findings provide a reference for the application of data mining in resource classification.

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Section: Figure 4 the Formal Description Model Of Landi Resourcesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Resource Classification and Knowledge Aggregation of Library and Information Based on Data Mining

Qin¹

2020

ISI

View full text Add to dashboard Cite

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A Review on Intelligent Library Services and Systems

Asemi¹

2023

Advances in Library and Information Science

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The chapter includes a comprehensive review of relevant published literature from the past five years. Through this review, the chapter explores the use of emerging technology-based services and systems such as intelligent libraries, recommender systems, fuzzy logic, and recommender system chatbots in the field of library and information science. The aim of this review is to provide up-to-date insights and information for professionals and researchers interested in utilizing these technologies to improve library services. The chapter highlights how these technologies can enhance the user experience and resource discovery. The chapter begins by introducing the concept of intelligent libraries and the role of emerging technology-based services and systems. It then explores the use of recommender systems and fuzzy logic in intelligent libraries, citing relevant published literature and discussing the benefits they bring to users. In the end, it discusses the potential challenges and limitations of these technologies, as well as best practices for their implementation and maintenance.

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Intelligent University Library Information Systems to Support Students Efficient Learning

Cited by 2 publications

References 21 publications

Resource Classification and Knowledge Aggregation of Library and Information Based on Data Mining

Resource Classification and Knowledge Aggregation of Library and Information Based on Data Mining

A Review on Intelligent Library Services and Systems

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