Knowledge Retrieval and Semantic Systems

Abstract The current research was conducted with the aim of explaining the information-seeking behavior of Allameh Tabataba'i University faculty members based on Belkin Episode Model for use in selective dissemination of information services. In terms of its nature and purpose, it was of an applied type and was done with a survey-analytical method. The studied population consisted of 562 faculty members of Allameh Tabataba'i University, and the research sample consisted of 226 people who were selected by stratified random method. The tool used for data collection was a semi-structured questionnaire. The validity of the questionnaire was confirmed by three subject experts, and the reliability of the questionnaire was estimated to be 0.90 by calculating the Cronbach's alpha coefficient. The collected data were analyzed using SPSS software. The findings of the research showed that the information-seeking behavior of faculty members is at an "average level" and is far from the desired level. As a result, it seems that the design of the databases, the suggested keywords and key phrases of databases, and the capabilities and facilities of the database search system for users for the purpose of conceptual searches should be designed more user-oriented to solve the information needs and improve the information-seeking behavior of faculty members. to help In addition, the faculty members' use of subject thesauruses in order to use specialized terms in order to retrieve information sources that match their information needs can also be a way forward.

Abstract purpose: The current research was conducted with the aim of investigating the impact of governance and digital leadership on the design and architecture of libraries .Methodology: The current research method is based on the purpose of applied type. Based on the method of data collection, this research is of mixed type. In this research, qualitative data and then quantitative data were collected and analyzed first, and priority is given to the qualitative phase.
Findings: The findings showed that the variable importance of digital leadership on the design and architecture of libraries has an average of 4.250 and the importance of digital governance on the design and architecture of libraries with an average of 3.786 has an average above average. In terms of compliance with the variable of digital leadership on the design and architecture of libraries with an average of 3.436 and the variable of digital governance on the design and architecture of libraries with an average of 3.321, it was above average. The research showed that the average of digital leadership and governance components in the design of library spaces is higher than the average of the Likert spectrum. Also, the significance level is less than 0.05, which means that the difference between the obtained averages and the average level is significant.
Conclusion: The results of the research showed that the components of digital leadership and digital governance were of high or very high importance from the point of view of experts in all subjects.

Abstract Goal: This research aims to explore the central role of language in the information retrieval process. It seeks to analyze the impact of syntactic structures, semantic features, and language differences between users and search systems on the accuracy and relevance of retrieval results. The study aims identify language barriers in translating information needs search logic and propose solutions to enhance convergence between user language and information retrieval.


Method: The data for this study was collected through an-descriptive approach, analyzing 00 scientific and specialized documents from information databases. These documents were selected on scientific quality, topical relevance, content diversity criteria. They were thenatively and quantitatively analyzed using syntactic lexical, and semantic indicators.
Findings: The research results that clear syntactic structures and precise word in user queries enhance the accuracy of systems. A significant portion of searchefficiencies stems from the gap between user language and structured system language. analysis and bridging the gap between natural structured language are key factors in information quality. The findings also suggested that analysis in information retrieval can benefit from language perspectives and meaning application theory.
Conclusion: This study has that language is not only a tool for expressing information needs but also a fundamental in shaping, interpreting, and processing. Simultaneously considering the syntactic, semantic and contextual dimensions of queries and improving mechanisms between natural and search languages can enhance the accuracy and efficiency of retrieval.

Abstract Objective:Schema.org has gained wide acceptance as a comprehensive standard for publishing structured data on the web. However,the general-purpose nature of this standard necessitates targeted enrichment to fully address thespecialized requirements of the publishing domain.A practical strategy for this enrichment involves establishing a mapping between Schema.org and domain-specific metadata standards such as ONIX,which has been explicitly designed for the publishing industry and commercial book distribution.This mapping, by identifying the representational deficiencies of Schema.org, paves the way for proposing lexical extensions aimed at enhancing its applicability in trade publishing.Accordingly,thisstudy aims to investigate the compatibility of Schema.org with the publishing domain based on the ONIX.
Methodology:The research employed a content analysis approach.The recording units comprised the classes and properties of Schema.org, while the semantic units consisted of the code lists of the ONIX.These code lists were systematically mapped against all Schema.org elements to identify corresponding and non-corresponding items.A checklist was utilized as the data collection instrument, and the data were gathered through structured observation.
Findings:Despite the divergent scopes and objectives of the two standards,which result in certain vocabulary mismatches,there exists considerable potential for interoperability.Schema.org lacks the comprehensiveness offered by ONIXin the commercial publishing sphere,indicating that this standard can serve as an efficient resource for enriching and augmenting the applicability of Schema.org within the publishing industry.
Conclusion:Aligning Schema.org with the ONIXenhances data integrity,semantic interoperability,and consistency across publishing workflows.This harmonization elevates the accuracy and reliability of semantic data publication,facilitates alignment with industry best practices,and ultimately strengthens the discoverability of published content within the SemanticWeb ecosystem

Abstract Introduction
The robustness of web scraping systems against structural changes in web pages remains a major challenge. Selenium-based solutions are highly vulnerable because they depend on fixed selectors. Existing robustness approaches often suffer from high computational costs or low reliability. To address this gap, this paper proposes an AI-based self-healing approach that dynamically analyzes element behavior and automatically selects the most suitable alternative selector, enabling continuous and reliable data extraction without manual intervention.
Literature Review
The studies by Kirinuki et al. (2019), Nass et al. (2023), and Coppola et al. (2025) propose alternative selectors to improve the reliability of web data extraction code using various cues. However, these methods exhibit relatively high error rates and are not suitable for pages with significant structural changes or elements with similar attributes. Although the use of large language models was proposed by Nass et al. (2024) to improve these methods and sometimes reduce errors, it raises privacy concerns and increases computational costs. In contrast, the present paper proposes a method that not only reduces errors but is also effective for pages with major structural changes while avoiding privacy and computational cost issues.
The works of Degaki et al. (2022), Khaliq et al. (2023), and Daneshvar and Wang (2024) propose using computer vision to predict elements on web pages. However, computer vision techniques show low accuracy in detection and prediction when the target information is limited, and they also involve high computational and time costs. In contrast, the present paper introduces a method that retrieves precise information while minimizing computational and time costs.
Taghizadeh et al. (2024) present a mechanism for time management and improving the accuracy of information retrieval from web platforms using Selenium. However, their method only identifies the location of errors and returns erroneous values as null, without providing a solution for code robustness. In contrast, the present paper builds on the method proposed by Taghizadeh et al. (2024) as a baseline for web data extraction and offers a solution for code robustness and automatic extraction of target values with the highest possible accuracy.
Saarathy et al. (2024) conducted a systematic review of existing studies on Selenium code robustness but did not propose a robustness model for web data extraction. In contrast, the present paper reviews existing studies and models and proposes a dedicated robustness model for Selenium code.
Healenium (2025) stores successful Selenium element information for future use but still requires manual intervention when errors occur. In contrast, the present paper automatically identifies alternative scripts using AI algorithms, reducing recovery time and human involvement.
Kluge and Stocco (2025) concluded that robust web scraping requires hybrid methods and automated validation, but they did not propose a new model. In contrast, the present paper introduces a model designed to overcome the limitations of existing approaches.
 
 
Methodology
This research presents an automated and robust framework for sustainable web data extraction (web scraping) that aims to overcome the inherent fragility of tools such as Selenium when facing structural changes in web pages. The proposed method is a hybrid system that integrates a relational database (SQL), Python and Selenium scripts, and artificial intelligence algorithms (particularly time-series models) to automatically identify and replace faulty selectors (XPath/CSS).

Data Infrastructure Design and Collection

Database: A SQL database was designed for structured storage, consisting of three main components:

Products table: stores extracted product information (name, price, discount, rating, image, label, and date).
HTML Tags table: records the complete tree structure (parent–child relationships) of HTML tags from the target website’s product pages (e.g., Digikala). This table includes the XPath (XML Path Language) of each tag, the extraction date, and a Boolean flag called “used”, which indicates whether a given XPath has previously been used successfully to extract a target element (e.g., a product name).
Tag Count View (virtual table): calculates the frequency of each unique XPath in the HTML tags table. This view enables the algorithm to prioritize XPaths that appear an expected number of times (e.g., 20 times on a 20-product page) as candidates for repeated elements (such as product names).


Extraction and Retrieval Engine

Primary Extraction Script (Selenium): A Selenium-based script was implemented to extract product information from target web pages using initially defined fixed selectors.
Structure Retrieval and Analysis Module: If the primary script encounters an error or returns empty results, this indicates a possible structural change in the page. In such cases, a backend script is triggered that:

Reads the full HTML structure of the page and processes it after removing static sections (e.g., headers and footers).
Uses regular-expression (Regex) algorithms to extract the full XPath of all tags and stores them in the HTML tags table.


Intelligent Decision-Making and Automatic Repair Layer

AI Models (Time Series): The core of the repair system is a predictive model that applies time-series algorithms (such as LSTM) to analyze the historical behavior of the “used” flag for each XPath. The model was trained on six months of historical data initially collected and labeled through manual supervision.
Iterative Repair Process: When an error occurs:

The model predicts and proposes replacement XPaths with a high probability of being marked as “used” in the future.
Candidate XPaths are inserted into the Selenium script in priority order, and the script is re-executed.
If execution succeeds, the corresponding flag is updated in the database. If it fails, unsuccessful candidates are discarded and the process continues with the next options.
If no solution is found, the system falls back to a full rule-based traversal of the tags table.


Validation and Output Quality Control

To ensure the accuracy of data extracted using alternative selectors, the system incorporates validation rules:

Quantitative validation: The number of extracted items for repeated elements (e.g., product names) must match the expected count (e.g., 20).
Qualitative validation (data patterns): Extracted data must conform to predefined patterns (e.g., product names as strings within a maximum length, discount percentages as numbers followed by a % sign, and labels from predefined categories).

Experimental Evaluation
The system was evaluated on the Digikala website over a two-year period with weekly intervals. Evaluation metrics included extraction success rate, requirement for manual intervention, execution time, and prediction model accuracy. Results indicate that the proposed system achieved near-complete stability, eliminated the need for manual correction, and reduced the worst-case average execution time to approximately 9 minutes for 60 products, demonstrating significantly higher efficiency compared to alternative methods (e.g., image-based approaches). The LSTM model achieved very high accuracy in predicting correct selectors in many cases.
Conclusion
This study presents an automated, AI-based approach for robust web scraping. By analyzing the HTML structure, systematically extracting XPaths, and employing intelligent decision-making algorithms (such as LSTM) to dynamically select alternative selectors, the inherent fragility of tools such as Selenium is mitigated. The results demonstrate that this method can significantly reduce the data extraction failure rate and eliminate the need for manual intervention. The proposed system, by learning from historical data, evolves into a semi-autonomous web crawler that ensures the sustainability of knowledge and data retrieval systems in organizational and research applications.

Abstract Introduction

Identifying access points to digital information resources and determining their importance from the point of view of specialists in each field plays an important role in retrieving the required resources. Knowing what retrieval points are used by researchers and experts to access digital information resources can have a positive effect on the redesign of information systems. The purpose of this research is to study and identify the importance of access points to digital information resources from the perspective of humanities researchers.

Literature review

Arastopour (1999) in a research aimed at investigating the problems related to access points in computer catalogs, states that changing the approach in computer catalogs can lead to the opening of new horizons in the discussion of the structure and display of records. Bevilacqua (2005) conducted a study at the University of Parma with the aim of investigating the organization of electronic journal titles from the perspective of humanities users, and stated that users provide multiple access points (such as inserting an alphabetical list of titles and a list of topics on the website) to electronic journals for more relevant retrieval. Abazari and Babaei (2013) found in their research that web page designers give more importance to metadata than specific metadata schemes such as Dublin. According to the research results of Rathi Tehrani & et al. (2013), from the point of view of experts, more than 70% of the elements of the standards were considered important and required for cataloging museum objects. Eichler & et al. (2021) compared existing metadata schemes and conducted studies on the production of metadata elements in a data management infrastructure. They concluded that an evaluation of existing metadata models shows that none are sufficiently general so far, as their design basis is not appropriate. Burke & et al. (2022) studied the available metadata and presented a model for organizing and creating a digital language archive based on people's characteristics. By studying 12 open-source metadata management tools, Singh and Madalli (2023) found gaps in metadata management programs and proposed a conceptual framework for research data management. Chapepa, Ngwira and Mapulanga (2023) investigated the methods of creating metadata in an academic data repository in the subject area of ​​agriculture and natural resources using the experts' point of view and found that the only metadata used was Dublin Core.

Methodology

The present research is practical. The method of conducting this research is survey-descriptive and has a case study approach. The research community in this work is the academic staff members of the Institute for Humanities and Cultural Studies. To receive the opinions and views of the academic staff regarding the access points, a researcher-made questionnaire with a reliability of 0.894 was used to collect the required data. The data collected through the questionnaires were entered into separate tables and analyzed through the Excel program.

Results

In terms of the importance of access points and retrieval fields of e-books, the subject, title, and main author are the most important fields of interest to researchers. In the field of lithographic books, the title, author and subject are the most important things, followed by the date of publication, calligraphy, and notes. The most important fields of attention of academic staff members in the field of searching manuscript books are title, author and subject, and the type of calligraphy and the main category are in the next ranks. The most important fields in the digital content of publications were title, call number, language and main topic. In the case of theses, the title, the author's field of study and the language of the work are recognized as the most important fields. The important fields for retrieving research projects from the point of view of academic staff members were the title, topic and employer of the project. The most important fields identified for retrieving digital documents are the subject, language and official title of the document. In terms of the importance of access points and retrieving fields of software and multimedia, the creator and subject are of the highest importance, followed by language, content duration, and file formats.

Discussion

From the point of view of academic faculty members, the most important access points for widely used types of digital content, such as e-books, lithographs and manuscripts, are the title, subject, and creator of the content. Regarding digital content in the form of publications, dissertations, theses, and documents, language and history are also important. Regarding different types, there are also significant cases that may show some kind of difference of opinion among the people of human sciences. For example, in the case of electronic books, whether there is a photo, picture, diagram, or table in a book is not very important for humanities experts, but the textual content is more valuable for them. Also, the year of publication of the e-book is not very important for the humanities experts, because most of the content produced in the humanities does not become worthless over time, or the translator of the works is of great importance for the people of the humanities. In the case of lithographic or manuscript books, calligraphy and calligraphers are noteworthy. The notes, which were not very important for humanities specialists in the normal book, are among the valuable items in these works because valuable information about the copies is included in the notes. Regarding the specific fields of digital resources, the file format of digital resources and their size are important items.

Conclusion

This research states that it is necessary to make changes in the design of user interfaces, the way of tagging and organizing digital content, as well as the arrangement and display of search results pages, according to the view of humanities experts. It is hoped that the results of this research will be useful for social catalogers in choosing appropriate access points and creating effective labels and tags for all types of digital content; for catalogers of digital resources in order to be aware of access points and important retrieval fields, to focus on it and save time and increase user satisfaction; for designers of information systems in order to define the file structure, organize pages for data entering, describe and organize digital resources, design pages and search facilities, develop search results customized facilities, design search results display pages; and for the managers of scientific-research websites in order to use access points and metadata elements in order to improve the accessibility of their digital content and facilitate the dissemination of digital information and improve the ranking of their websites.

Abstract Introduction

The management of digital resources in national libraries involves significant challenges, particularly in selecting, maintaining, and ensuring long-term accessibility. A crucial element in this process is the storage format of digital resources, which directly affects both the preservation of materials and their usability over time. Below are key reasons why the choice of resource storage formats is important for national libraries:

Long-Term Preservation: National libraries manage vast collections of digital materials, from texts to multimedia resources. Choosing a storage format that ensures long-term preservation is essential to prevent data loss over time due to format obsolescence. National Libraries often face challenges of format obsolescence. The right choice of format can minimize the need for complex emulation or migration strategies, which are resource-intensive.
Interoperability and Accessibility: Digital collections in national libraries need to be accessible across various platforms, devices, and operating systems. International standards and guidelines, such as those from the International Federation of Library Associations and Institutions (IFLA), guide the choice of formats that facilitate interoperability. Adopting these standards ensures that digital resources are accessible not only to national users but also internationally. This is especially important for cultural heritage materials that may be used globally.
Efficiency in Storage and Retrieval: When dealing with large-scale collections, efficient storage formats help minimize infrastructure costs. The speed at which data can be retrieved from a storage system is influenced by the format of the resources. Formats that are optimized for efficient access improve search and retrieval times, facilitating quick access to resources for users.
Metadata Preservation and Integration: National libraries depend heavily on metadata to ensure that digital objects are easily discoverable and appropriately categorized. Standardized formats are crucial for integrating digital collections with national library cataloging systems and facilitating interoperability between different systems. National libraries must ensure that the digital resources they store are secure and protected from corruption.
User Experience and Engagement: National libraries serve diverse audiences, ranging from academic researchers to the general public. Formats that are easily navigable (e.g., HTML or EPUB for e-books) improve user engagement and accessibility. Interactive or multimedia content (e.g., video, audio) in open formats can provide richer, more engaging experiences. Formats like Unicode-based text formats (e.g., UTF-8) allow for the preservation of multiple languages and scripts, making national library collections accessible to diverse communities, including those with specific linguistic or cultural needs.
Legal and Copyright Considerations: Formats may also play a role in how digital rights and licensing information are embedded and protected. Open formats allow for the inclusion of rights management information without reliance on proprietary systems, ensuring proper management of copyrighted materials. The use of appropriate formats for the digital storage of copyrighted content can aid in enforcing digital rights management (DRM) policies. Formats like encrypted PDF or DRM-protected EPUB help libraries protect content according to legal guidelines.
Cost-Effectiveness: Choosing the right storage formats can have a significant impact on cost management for national libraries. Open-source and standardized formats tend to be cost-effective compared to proprietary systems that may involve licensing fees, additional maintenance costs, or vendor lock-in. National Libraries must invest in ensuring the longevity and accessibility of their digital collections. By choosing widely accepted formats with strong community support, national libraries can reduce ongoing maintenance and conversion costs associated with less popular or proprietary formats.

So, the importance of selecting the right resource storage formats in national libraries cannot be overstated. A well-chosen format ensures the long-term preservation, accessibility, and efficient management of digital collections. It also contributes to the overall mission of national libraries to serve as custodians of cultural heritage, making materials accessible to a global audience while protecting them for future generations. Standardized, open, and widely supported formats are crucial in meeting these objectives, enabling national libraries to optimize their digital storage solutions while maintaining flexibility, cost-effectiveness, and long-term sustainability.

Literature Review

The results of Sullivan (2006), Thomas & Martin (2006), Hodge & Anderson (2007), Rog & Van Wijk (2008), Van der Knijff (2011), Barabucci & et al (2011), Morrissey (2012), Hajtnik (2012), Jackson (2012), Koo & Chou(2013), Rimkus & et al(2014), Uherek & et al (2015), Termens & et al (2015), Delaney & De Jong(2015), Baratè & et al (2015), Rimkus & Witmer (2016), Anyim (2021), Trianggoro & Prasetyadi (2022) research showed selecting the right format and storage standard for digital collections is a multi-faceted decision that balances accessibility, preservation, interoperability, and user experience. Ensuring that digital collections are presented in a way that aligns with these standards maximizes their utility and longevity. It highlights that while digital libraries have evolved from physical spaces, the principles and practices of resource storage have undergone significant changes. Previous research has addressed these issues, but often as sub-components rather than focusing on them comprehensively. The review indicates that long-term preservation and storage have not been fully explored in the literature.This research aims to identify successful national solutions for preserving and storing resources effectively in digital libraries. In essence, the study seeks to provide a more integrated approach to addressing storage and preservation issues in digital libraries, taking into account both the technological and organizational practices in use today. This effort is important for ensuring that digital resources remain accessible and usable over time, despite the challenges posed by rapid technological change and shifting formats.

Methodology

This article identifies the use of a variety of standard formats for storing video, text, multimedia, and audio resources in the digital collections of 20 selected national libraries around the world. This study is applied, based on the descriptive-analytical method. For data collection, we used a researcher-made questionnaire. After collecting data, a variety of descriptive statistical techniques such as frequency distribution and frequency percentage and Chi-square test were used to analyze the data.

Results

Based on the results, it was found that image sources were used in all studied collections and cultural objects were less popular with a share of 41%, for TIFF image sources (94%); HTML and XML text sources (75%); WAV audio sources (65%) and AVI multimedia sources (65%) were the most common. Switzerland had the greatest variety in the use of a variety of standards. Also, among the research community, Iran, Britain, the United States, Scotland, Qatar, the Netherlands, France, and Spain had the greatest diversity in storing a variety of digital resources. The statistical community was consistent in using standard formats for a variety of visual, textual, and multimedia resources and followed a similar pattern in selecting storage formats.

Conclusion

The research community had the least amount of diversity of use in the field of multimedia resource storage. Research findings emphasize the use of EPUB for ease of reading books on e-readers, and GP3 was recommended to increase the usability of the mobile version of the digital library, WARC as a special format for web archiving, for long-term protection of digital content of national libraries, because these three formats had the lowest usage in the statistical community.
Acknowledgments
The authors are grateful to Michael Day (Digital Preservation Research Lead) at the National Library of Great Britain for her guidance and sharing of scholarly expertise.

Abstract This study investigated the information-seeking behavior of art researchers in the process of searching for information on the web. This study is semi-experimental. It was conducted using observation, interview, and statistical analysis methods. The statistical population consisted of 48 art researchers who were selected through purposive sampling. Data were collected through Camtasia software to record the search process, semi-structured interviews to examine cognitive strategies, and a standard information-seeking behavior questionnaire to measure related variables. Two search tasks were assigned to the participants: easy (finding a Latin article about Iranian art) and difficult (finding a related job opportunity abroad), and data analysis was performed using the Chi-square test. The findings showed that in easy searches, participants mainly used faster and more superficial strategies such as extensive use of the Google search engine (with a frequency of 976) and formulating search terms from general to specific. In contrast, in difficult searches, researchers resorted to more advanced analytical methods such as repeated modification of search terms, use of Boolean operators, and reference to specialized databases. The statistical data analysis showed that the total number of strategies adopted in the second task was 976 in the easy style and 959 in the difficult style, for a total of 1935 strategies, indicating that the level of complexity of the search tasks has a direct impact on the strategies used by researchers. This highlights the need to optimize information retrieval systems based on the needs of users and the level of complexity of their searches.

Introduction

This study examines the information-seeking behavior of art researchers when dealing with simple and complex search tasks. Due to the interdisciplinary nature of the field and the need for multimedia resources, researchers face specific challenges in accessing information. Using a semi-experimental approach and employing observation, interviews, and questionnaires, the study aims to contribute to the development of more efficient information systems and specialized training for this user group.
 

Literature Review

Information seeking behavior is a key concept in information science and human interaction with information sources that has attracted significant attention from researchers in interdisciplinary fields, especially art, in recent years. Previous studies have shown that various factors, such as the complexity of search tasks, users' previous experiences, cognitive styles, and familiarity with tools and databases have a significant impact on the way people search for information (Savolainen, 2018; Mitsui et al., 2017; Humbhi & Tareen, 2022). In this context, information-seeking behavior in the field of art is associated with specific challenges such as the need for non-textual sources, multimedia content, and interdisciplinary approaches that have been less systematically studied (Pergantis et al., 2023; Masinde et al., 2020). In addition, examining the role of psychological variables such as self-efficacy, anxiety, and metacognitive strategies in the information seeking process has also been considered in some studies (Noorzadeh and Noormohammadi, 1400). Recent findings emphasize the need for a deeper analysis of researchers' interaction with information retrieval systems and the factors affecting the choice of search strategies.

Methodology

This study employed a semi-experimental design to investigate the information-seeking behavior of 48 purposively selected art researchers. Data collection included search file analysis, event recording, and behavioral observation using Camtasia Studio. Participants, all holding a master’s or doctoral degree in an art discipline and with prior research experience, were assigned two tasks: a simple search (finding a Latin article on Iranian art) and a complex one (finding an international job related to their field). Selection criteria also included adequate computer skills and willingness to participate.

Results

In order to conduct the research, the researcher assigned two types of search tasks to the subjects and observed and analyzed their behavior and perspectives during the information search and retrieval process. The methods of observing the respondents' information search and retrieval behavior and search tasks are as follows:

a) Search tasks: In this study, search tasks are divided into two categories: easy and difficult. In the easy task, the user searches for general information about a general topic, and in the difficult task, the user seeks specialized information about a specific topic. The easy search task is usually accompanied by the continuous use of browsing, while the difficult search task requires the use of analytical search strategies. In the present study, these two tasks were characterized by general and specialized levels. Therefore, in the easy task, the minimum level of complexity was considered, and in the difficult task, there is more complexity. All searches performed by users were recorded with the help of computer screen capture software (Table 1).

b) Observation: It refers to the process of identifying, recording, naming, comparing, and analyzing what is happening. The key point in conducting an observation is to accurately and completely define the subject being observed.

The entire process of searching and retrieving information by each subject was recorded using screen capture software. Necessary notes were taken of each subject's searching process by reviewing the captured files several times and taking notes of the searching and retrieving information process.

Discussion

This study explored how art researchers adapt their search strategies based on task complexity, revealing that simpler tasks led to basic, fast-paced techniques (e.g., broad queries via Google), while complex tasks triggered more advanced approaches like iterative refinement and the use of specialized databases. Although strategy frequency was similar across tasks (976 for simple, 959 for complex), statistical analysis confirmed significant behavioral differences linked to task difficulty. The findings highlight the need for adaptive, user-centered search systems and targeted training in digital literacy. Consistent with prior research, the study emphasizes the influence of cognitive and experiential factors, advocating for further inquiry into psychological variables and intelligent search system design to better support art researchers.

Conclusion

This study concludes that task complexity significantly influences the search strategies of art researchers, with simple tasks leading to intuitive methods and complex ones requiring more analytical approaches. The results stress the need for adaptive, user-focused information systems and specialized training to strengthen digital search capabilities. Future research should consider cognitive and psychological aspects to deepen insights into search behavior and improve information retrieval in the arts.
Acknowledgments
I extend my deepest appreciation to Dr. Zohreh Mirhosseini for her exceptional guidance, insightful feedback, and unwavering support, which played a pivotal role in the successful completion of this study.

Abstract Introduction

Recently, the development of artificial intelligence and human-computer interaction has highlighted the increasing importance of language challenges in information retrieval. The crucial role of language in disseminating, accessing, and retrieving information cannot be studied independently of syntax and semantics. Explaining and describing research in this field from both quantitative and qualitative perspectives, and understanding researchers' trends, is an important step in comprehending the significance of syntax and semantics in communication structures within modern information search and retrieval environments. Consequently, in this descriptive and analytical study, we conducted qualitative and quantitative analyses of studies in the field of syntax and semantics in information retrieval.

Literature Review

In recent years, there has been a lot of interdisciplinary research focusing on investigating the impact of language on the interaction between users and the web environment. These studies have discussed the language from various perspectives and have explored information retrieval across different types of information media, including web databases, search engines, commercial websites, and libraries. Tapsai (2019), Norouzi and Hamavandi (2018), Hammo (2009), Lazarinis (2008), Ofoghi, Yearwood & Ghosh (2006) have focused on different languages such as Persian, English, Arabic, and Greek. The findings show that the syntax and morphology, as well as the semantics of searched terms and phrases, have a significant impact on the retrieval of results. In addition, search tools tend to rely more on the general form of words instead of focusing on the real needs of users in order to improve the search process.
Due to the huge amount of information on the World Wide Web and the challenges related to information retrieval, researchers and software developers have turned to the Semantic Web to keep up with the changes. The Semantic Web has provided a large amount of structured and machine-understandable information on a wide range of topics (Guha, McCool & Miller, 2003). Semantic models perform well in identifying and recognizing synonyms, similar words, and semantic frameworks. Therefore, one of the most important challenges in the field of information storage and retrieval is to bridge the gap between the language used by information seekers and information providers (Rezaee Sharifabadi et al., 2010).
The current study aims to systematically review previous research findings on syntax and semantics in information storage and retrieval across different contexts. Each context represents different dimensions of knowledge representation systems, from traditional to semantics. Upon reviewing the research, it was found that no systematic review has been conducted with a focus on syntax and semantics in the field of information retrieval.

Methodology

In this qualitative research using Aveyard’s systematic review method, we aim to address the following questions:

What is the statistical status of studies in the field of syntax and semantics in storing and retrieving information?
What are the main subject areas that researchers have focused on in studies related to syntax and semantics in storing and retrieving information?
What research methods and approaches have researchers employed in this field?
What are the research gaps and areas that require further study in this field?

To gather relevant sources from information databases, we selected search keywords based on the research questions. Then, we used search strategies and various operators to combine the keywords and phrases, ensuring a comprehensive and effective search in Persian databases such as Magiran, Irandoc, SID, NoorMagz, ISC, and Civilica, as well as databases including Scopus, Emerald, ProQuest, and Google Scholar. There was no time limitation for the search. We recorded accepted sources such as articles and theses that were relevant and valid. By removing irrelevant and duplicate sources, we selected 12 Persian sources and 42 English sources. After categorizing, the studies were analyzed according to the type of source, research method, and tool. The results of the analysis of the studies were presented in the form of tables and graphs.

Results

The selected studies were categorized into three groups (their characteristics were described in detail): information retrieval, information organization, and information search based on the analysis of keywords and subjects raised in the sources. The results of the study revealed that among the 54 reviewed studies, Iranian researchers had conducted the most research in the field of syntax and semantics in information retrieval, with 12 studies. The United States followed with 5 studies, and China and Vietnam tied for third place with 4 studies each. The majority of the studies focused on syntax and semantics in information retrieval.

Discussion

Analysis of 54 selected studies has shown that these studies were conducted over a period of 26 years. The oldest study was included in the review back to 1997, while the most recent one is from 2022. This shows the dynamic nature of the field under investigation and demonstrates how it is constantly changing and being influenced by the advancement of web technologies. Furthermore, a thematic analysis of the research, based on the studies' keywords, reveals that "Ontology," as a tool of the semantic web, is closely linked to the semantic and syntax aspects of language in information retrieval.
Moreover, in a total of 54 studies, the majority were experimental (19), followed by applied (15) and analytical (9). Additionally, there were 6 studies that combined applied and analytical methods. Content analysis and comparative analysis each had 2 instances, while case studies were the least frequent with only 1 case. These studies have utilized tools such as ontology, search engines, and techniques including natural language processing, annotation, tagging, and indexing.
The discussion about exploring syntax and semantics in relation to information retrieval across different languages is believed to make a significant contribution to the development of future research literature in this field. This is because users’ native language plays a central role in forming search terms for information retrieval, based on subjective meanings, context, and content. Considering this point can effectively enhance information retrieval systems.

Conclusion

Although many studies have addressed various aspects of syntax and semantics in information retrieval, more research is needed to investigate syntax and semantics in information organization. It is also important to delve into and analyze their theoretical aspects in information retrieval, especially through interdisciplinary studies.
Moreover, the interconnectedness of various areas of study demonstrates the close relationship between syntax and semantics and linguistic issues in nearly every field that involves organizing, storing, and retrieving information. These areas include the study of syntax and semantics in relation to environmental sensors, indexing, identification and summarization of texts, plagiarism detection, natural language processing, repositories, improvement of query users and data retrieval in repositories and search engines, metadata enrichment, and image retrieval. The results of this research, such as its main themes, identified methods and approaches, and research gaps, can offer valuable insights for future studies.

Abstract Introduction
The field of providing information and the method of publishing information has permanently been subject to modification and alteration, and as we know, with the introduction of computer technology in the field of librarianship and the change in the way of providing services, the imperative task of information dissemination has been reserved for librarians (Kanjilan,2011).Due to the nature of their job, librarians must be interested to changes and change their services and the way they provide services at the same time and in agreement with the changes, so that they can respond to the information needs of the residents(Mohammadi Fard,2015).Nowadays, with the development of new information technologies and the challenges of information societies, the traditional role of public libraries has changed and functions such as teaching and creating computer skills have become more projecting. Thus, librarians of public libraries should initially, be prepared with these skills. A librarian who is not computer literate will never be a good guide for library users. The inability of individuals to access information and their limited knowledge in using computers can hinder their success in retrieving information. Hence, enhancing computer literacy is particularly essential for these individuals. Education can play a crucial role in improving their computer skills (Abtahi,2017). One form of instruction is electronic training, also referred to as e-learning or virtual learning. This type of learning involves online courses provided through a virtual education system, enabling electronic learning processes(Ghalian & Zalpour,2018). The objective of this study was to examine the impact of electronic information retrieval training on the information retrieval abilities of librarians.

Literature Review
Kia, Moazzami, and Kia Lashaki (2021) in a study entitled: “Examining the influence of virtual skills training during the COVID-19 pandemic on the performance of Chalous Scientific-Applied University graduates” concluded that virtual skill training has a positive and significant effect on the performance of graduates in the Corona era, and the regression equation was also presented to predict the effect of the predictor variable on the criterion variable. Mohaghegh, Raiesi Dehkordi, Alibeik, Ghashghaee and Janbozorgi (2017) showed that consistent with the employees' attitude towards participating in in-service virtual training courses, their satisfaction along the course and the productivity of the topics discussed in these courses, from the point of view of librarians, the effectiveness and quality of in-service virtual training courses are at the favorite level.
Al-Fraihat, Masa'deh and Sinclair (2020) showed there are four structures influencing the use of e-learning, the quality of the educational system, the quality of the support system, the quality of the learner and the perceived usefulness, which together account for 1.34% of the variance. Finally, 64.7% of the variance of e-learning benefits is explained by supposed usefulness, alleged satisfaction, and use. Maurice (2017) showed that there is a positive and significant relationship between virtual training and employee empowerment, and employees who did not participate in in-service training are less empowered than those who participated in these courses.

Methodology
The current research was of the type of applied research and the method of conducting the research was of an experimental type with a pre-test and post-test design with control and experimental groups. The statistical population of this research included all the librarians of the public libraries of Mazandaran province in 1401 in the number of 285 people (taken from the statistics center of the general administration of the public library of Mazandaran province). After the homogenization of the statistical population geographically (Mazandaran province was divided into three parts, east, central and west) and from each part according to the inclusion criteria such as willingness to participate in training sessions at certain hours, being librarians of public libraries in Mazandaran province, having a bachelor's degree, having an age between 25 and 40 years, working experience of more than 5 years in a library, obtaining a score below 39 from the questionnaire and exit criteria including not working in public libraries in Mazandaran province, having a bachelor's degree and obtaining a score above 39 from Questionnaire, first, 30 people were selected by purposive sampling method and they were randomly divided into two groups of 15 people, experimental and control. The experimental group received information retrieval skills training in 9 sessions (each session lasting 2 hours) electronically and remotely. But the control group did not use any training. In order to measure the information retrieval skills of librarians, due to the lack of a standard scale, a researcher-made questionnaire was used. The content validity of the questionnaire was confirmed. Also, its reliability was calculated using Cronbach's alpha coefficient of 0.89 in a test run.

Discussion
The findings displayed that the average skill of information retrieval in the experimental group (47.07) in the post-test is higher than the average in the control group (26.86). which indicates that, electronic information retrieval training has an effect on the skills of librarians in information retrieval. In the explanation of the research findings, it can be stated that electronic training allows people to obtain scientific information in less time and at a cheaper cost and it increases its generality and also causes rapid learning of skills in various dimensions. The internet is an easy way in the new age to get up-to-date and new articles and information for learning and empowerment. In other words, the availability of the Internet makes it possible to obtain new information in less time, and in the context of librarians' use of new methods and patterns in information retrieval, it surges their skill in information retrieval.

Conclusion
The results of the research showed that electronic information retrieval training has a positive and significant effect on the skills of librarians in information retrieval, and electronic information retrieval training can be one of the effective options in increasing the capabilities and skills of librarians.