Knowledge Retrieval and Semantic Systems

Abstract Objective: The primary objective of this research is to analyze the capabilities of Quantum Information Theory (QIT) in improving information retrieval processes. The study seeks to address how the fundamental principles of quantum mechanics can be leveraged to overcome the challenges inherent in traditional information retrieval systems.
Methodology: This study was conducted using a library method with an analytical-review approach. Through a comprehensive review of theoretical literature, the foundational concepts of QIT were identified, and their conceptual and practical relevance to the field of information retrieval were systematically analyzed.
Findings: The findings indicate that Quantum Information Theory, through concepts such as superposition and entanglement, provides a new framework for information representation, processing, and retrieval. The application of phenomena like quantum algorithms and quantum error correction can significantly increase the accuracy and speed of information retrieval. By unifying the representation, ranking, and cognitive aspects of the user, this approach offers solutions for developing more dynamic and context-aware systems.
Conclusion: Despite existing technical and theoretical obstacles, Quantum Information Theory holds the potential to fundamentally transform the field of information retrieval. It is anticipated that with continued research in this area, innovative technologies based on quantum principles will be developed, leading to enhanced efficiency, security, and precision in future information retrieval systems.

Abstract The purpose of this study is to analyze the semantic information search behavior of faculty members at Shahid Modarres Hospital in the PubMed database regarding COVID-19, based on Ingwersen’s model. This applied study employed a quantitative approach using a descriptive-analytical survey method. The statistical population consisted of faculty members at Shahid Modarres Hospital. Data were collected using a researcher-made questionnaire and analyzed utilizing SPSS software (version 25). 52% of respondents are satisfied with automatic keyword suggestions in PubMed. 67% agree with using the MeSH main topics filter, but only 44% use MeSH subheadings as a more precise tool for semantic searching. The PICO tool has a weak position in users' search behavior, with only 35.2% agreement. Nearly 60% emphasize the role of synonyms in enriching search. 68.6% find suggested keywords useful as a tool for developing their semantic search, and 79.6% recognize abstracts as the key to assessing the relevance of results. Moreover, there are significant differences in semantic search behavior based on academic rank, years of service, and specialty vs. subspecialty status. The difference based on gender is not significant.
In addition to the features of the retrieval system, user search behavior is influenced by individual cognitive factors as well as social and organizational contexts. Therefore, enhancing training on advanced search skills and familiarity with PubMed’s conceptual tools can improve the quality of semantic searches, increase retrieval efficiency, and more effectively support scientific and clinical decision-making.

Abstract The primary objective of this study was to develop a comprehensive model for fostering AI-driven data science literacy among students. Utilizing a meta-synthesis approach and a theory-building qualitative method, the research integrates precursors, processes, and outcomes into a unified framework. A systematic search was conducted using keywords such as "data science literacy," "artificial intelligence," and "machine intelligence" across prominent international databases (Wiley, ScienceDirect, Taylor & Francis, ProQuest, Scopus, and Emerald) as well as Persian databases (Magiran, Noormags, and SID). Following a rigorous screening process, 77 articles were selected for final analysis. Data were analyzed through grounded theory using open and axial coding. The findings revealed that the precursors of AI-driven data science literacy comprise three main themes: theoretical and strategic curriculum frameworks, teacher competencies, and student competencies (encompassing 59 open codes). The process of literacy development is structured into seven main themes supported by eight specific categories of digital tools and platforms. Additionally, the outcomes are classified into three core dimensions: academic-cognitive, metacognitive-affective, and social-ethical (spanning 15 open codes). The results indicate that this model empowers students for informed and responsible participation in a data-driven society. Ultimately, the study emphasizes that achieving robust data science literacy necessitates data-centric curricula and sustained professional development for teachers to transition from traditional roles to AI-augmented learning facilitators.

Abstract This study analyzes the knowledge structure and research trends in Agile Data Management (ADM) within the banking industry. Using a bibliometric approach, this study identifies key authors, conceptual clusters, lexical trends, and international collaborations in this field, providing a comprehensive picture of the current and future state of related research. For the analysis, data from Scopus, including 552 articles published between 1980 and 2025, were extracted. Analysis tools included VOSviewer and the Bibliometrix software package in R. Analysis types included synonymy, co-authorship, co-citation, and bibliographic pair analysis. Only full-text, English-language, and research articles were included in the analysis. Conceptual Clusters: Five main clusters were identified: digital transformation, emerging technologies, customer behaviour, knowledge management, and sustainable development. Authors and countries: India, Indonesia, and Malaysia have published the most articles. Authors such as Khorsand and Soldatos were identified as key players. Trends: Concepts such as “blockchain,” “digital transformation,” and “smart banking” have seen the most growth. Networks of collaboration: South-South (India-Jordan-Indonesia) and Western regional collaborations are prominent in developing theoretical frameworks. This study shows that agile data management, as an interdisciplinary field, is growing rapidly and is increasingly critical for banks. The results of this research can serve as a basis for policymaking, the development of agile infrastructure, and the direction of future research in digital banking.

Abstract Purpose: This study aims to investigate the role of public librarians and agricultural experts in the documentation and retrieval of indigenous saffron knowledge in South Khorasan, Iran.
Methodology: The study employed a qualitative case study approach. Data were collected through unstructured interviews with public librarians (20) and agricultural experts (10) in South Khorasan using purposive sampling. The interviews focused on indigenous knowledge documentation practices, retrieval mechanisms, existing challenges, and proposed solutions. Data were analyzed using qualitative content analysis through open, axial, and selective coding.
Findings: The findings revealed that indigenous saffron knowledge is primarily documented through oral narratives, interviews with experienced farmers, multimedia documentation, written resources, and local archives. Retrieval practices included digital repositories, information systems, metadata organization, digital libraries, and information mediation. The study also identified several challenges, including weak technological infrastructure, limited institutional collaboration, lack of participation, and the gradual loss of indigenous knowledge due to ageing knowledge holders. The findings further emphasized the importance of educational empowerment, digital infrastructure development, participatory documentation, inter-organizational collaboration, and culturally sensitive knowledge management practices.
Innovation/Value: This study contributes to the limited literature on indigenous agricultural knowledge management in Iran by focusing specifically on indigenous saffron knowledge in South Khorasan. It also highlights the collaborative role of librarians and agricultural experts in the preservation, organization, and retrieval of indigenous agricultural knowledge.
Conclusion: The study concludes that sustainable preservation and retrieval of indigenous saffron knowledge require integrated collaboration among libraries, agricultural institutions, local communities, and digital information systems.

Abstract In the era of rapid technological transformations, users’ ability to understand, analyze, and reconstruct their technological relationships plays a crucial role in determining their level of digital resilience. The present study aims to examine the gap between knowledge and performance in digital resilience literacy and to identify users’ active coping strategies when facing crises in digital environments.The research employed a qualitative design based on the grounded theory approach. Data were collected through semi structured interviews with 25 participants from the community of social media activists (including civic and media activists) on Instagram. The data were analyzed through three stages of open, axial, and selective coding.Findings revealed that the knowledge gap in digital resilience literacy mainly stems from superficial perceptions of technological risks, cognitive dependency on platforms, and insufficient algorithmic literacy. In contrast, the performance gap arises from the inability to reconstruct adaptive technological behaviors and weaknesses in digital emotion regulation.Three main dimensions of active coping strategies were identified: (1) reflective learning and self regulation; (2) reconstruction of digital identity in the face of data crises; and (3) utilization of supportive and techno collaborative networks.The results indicate that advancing the concept of digital resilience literacy as a key competence for modern technological life contributes to understanding resilience not merely as an outcome of education, but as a continuous process of learning, reflection, and technological self reconstruction.

Abstract The aim of the study was to identify the challenges of using artificial intelligence in the process of knowledge acquisition of students at Farhangian University of Kurdistan Province and the solutions to overcome the challenges. The critical paradigm of the qualitative approach and the Colaizzi phenomenological were used. The research field included students at Farhangian University. Data collection was carried out through semi-structured interviews. A total of 32 students were interviewed through purposeful and criterion-based selection and with the criterion of data saturation. The findings were analyzed through inductive analysis of written text. The findings were presented in two sections: challenges of using artificial intelligence for students' knowledge acquisition and solutions to overcome the challenges. The challenges section was presented in two areas: creating challenges for the position of knowledge acquisition and retrieval of scientific information and creating challenges in the quality and quantity of knowledge acquisition and retrieval. Also, solutions to overcome these challenges were addressed in two areas: solutions at the individual level and solutions based on the organizational and educational environment of Farhangian University. Analysis of the findings showed that, along with numerous benefits for acquiring and retrieving knowledge, artificial intelligence can shake the mindset of Farhangian University students regarding its status and reduce their scientific and skill abilities; therefore, the way to use this tool requires management, culture building, and grounding. In this regard, , a suitable ground can be provided for the use of artificial intelligence in acquiring knowledge at this university.

Abstract he purpose of this study was to investigate the relationship between information literacy with organizational creativity and job performance of public librarians in Kermanshah province.
This research has been done by descriptive-correlation method. The statistical population of this study consists of all librarians of public libraries in Kermanshah province (170 persons). Based on Cochran formula, 118 individuals were selected as sample. The sampling method used was stratified random sampling. Three standard questionnaires were used to collect data: Qasemi Information Literacy (2007), Dorabaji et al (1998) and Paterson Job Performance (1970). The reliability of the questionnaires was calculated using Cronbach's alpha coefficient and was 0.81, 0.93 and 0.97, respectively, indicating that the questionnaires have a good reliability. Descriptive indices, Pearson correlation coefficient and Sobel test were used to analyze the data and test the research hypotheses.
The results showed that librarians who are more creative and high performing, have more information literacy, and can achieve higher goals. Therefore, it can be said that increasing information literacy among librarians makes them more creative and enhances their job performance and consequently improves the performance of public libraries.
Based on the results,it can be said that increasing information literacy among librarians makes them more creative and enhances their job performance and consequently improves the performance of public libraries. As a result, Kermanshah Public Library Managers can improve the information literacy of librarians, Enhance their organizational creativity and career performance and improve the performance of their public libraries under their management.

Abstract The aim of the study was to investigate the effectiveness of teaching personal information management using the flipped classroom method on reducing information anxiety and academic procrastination among students of Farhangian University. In terms of purpose, this research is applied, and based on the data collection method, it is a quasi-experimental study with a pre-test and post-test design with a control group. The research population consisted of all students at Farhangian University,from which 30 individuals were selected through simple random sampling and randomly assigned to two groups: an experimental group (15 individuals) and a control group (15 individuals). The tools used for the pre-test and post-test included the questionnaire developed by Imanzadeh and Morandi Heydarloo (2023) and the Academic Procrastination Scale by Solomon and Rothblum (1984). The designed training package, after approval by the respected advisors and experts in the field of information science, was confirmed for content validity. The training package was delivered to the experimental group in 10 sessions of 60 minutes each. In the descriptive statistics section, indicators such as frequency, mean, and standard deviation of scores were used, and in the inferential statistics section, multivariate analysis of covariance (MANCOVA) was employed to analyze the data. The findings of the study indicated a significant difference between the mean post-test scores of the experimental and control groups in the variables of information anxiety and academic procrastination, demonstrating that teaching personal information management using the flipped classroom method was effective in reducing information anxiety and academic procrastination among students.