پژوهشنامه پردازش و مدیریت اطلاعات
سال سی و نهم شماره 1 (پیاپی 115، پاییز 1402)

Knowledge map is a KM tool, through which it is given to the organization's users, information about the location of knowledge deployment and knowledge resources ranging from people possessing knowledge, documents, and databases. Knowledge map determines the expertise and knowledge required by people with the location of its deployment in the organization, the main purpose of this study was to map the knowledge and skills of the librarians of Astan Quds Razavi Central Library based on Max Weber's Ideal Type Model.

This study was of an applied form and its procedure was descriptive-analytic survey. The population included 39 librarians working at the Central Library of Astan Quds Razavi who had studied knowledge at Associate degree, in Knowledge and information science, in Knowledge and information science and had a librarian's Position. Researcher’s made questionnaire was used as the data collection instrument and the rate of return was 100 percent. In addition to the questionnaire, the checklist created by Shamsi (2012) was used by the researcher in order to collect data.

The findings showed that in the general skills section of librarians, the highest mean was related to administrative abilities such as office automation, text editing ability, etc. (mean 2.53), and librarians in language skills (mean 1.03), Accounting (mean 0.55) and computer (mean 2.33) have knowledge gaps. In examining the specialized knowledge and skills required of different sections of the central library of Astan Quds Razavi, it was found that the librarians had the knowledge and skills needed to work in the study halls sections (3.89 on average), and the library (with an average of 3.89). Library circulation (4.2), membership (mean 3.77), cataloging (mean 3.42), collection (mean 3.25) and audiovisual mean (mean 3.79), and librarians have a knowledge vacuum for working in the digital library (2. 63 average) and stencils (1.68 average).

Findings from the Librarian Knowledge and Skills Index based on the Ideal Model showed that most librarians (22) were in Type 1 (High Knowledge and Skills). On the one hand, none of the librarians are in Type 2 (high knowledge and low skill) librarians, and 12 in Type 3 (low knowledge and high skill), and 5 in Type 4 (low knowledge and skill)Keywords: Drawing knowledge map, Max Weber Type Ideal Model, librarian, Astan Qods Central Library

During the last two decades, some international treaties have played a decisive role in facilitating scientific collaboration between member countries. For this reason, the study aims to predict the effect of Iran's membership in these treaties on three things: First, the amount of scientific collaboration between Iran and the members of each treaty; Second, the total amount of Iran's international scientific collaboration; Third, the extent of Iran's dependence on scientific collaboration with the USA, as the most key actor in the international scientific collaboration network. According to the background, the treaties that have a significant impact on international scientific collaboration are G7, G20, EU, OECD, OPEC, APEC, and BRICS. This study is based on the simulation method (with an agent-based modeling approach). This method was used to simulate the network of scientific collaboration between independent countries with more than one million people in the period of 2023-2042. The secondary data required for the simulation were collected from the Web of Science database and the United Nations database. Hypotheses related to possible scenarios were tested based on difference-in-difference statistical model. All calculations, including network simulation and hypothesis testing, were performed in the R software environment. The findings showed that Iran's joining G20, OECD, and APEC will significantly increase Iran's scientific collaboration with the members of each treaty. However, Iran's membership in the BRICS will not have a significant effect on its collaboration with the BRICS members. Also, Iran's joining each of these four treaties will significantly increase the total amount of Iran's international scientific collaboration. However, the increase in the G20 scenario is higher, and in the BRICS scenario is lower than other treaties. At the same time, Iran's membership in the G20 and BRICS will lead to a significant increase in Iran's dependence on collaboration with the USA. In return, Iran's membership in the OECD and APEC will play a significant role in reducing Iran's dependence on collaboration with the USA. Another advantage of Iran's membership in the OECD is strengthening its collaboration with two of the key players in Europe (France and Italy). One of the side benefits of Iran's joining APEC is the significant increase in its collaboration with the key player in East Asia (China). The results indicated that Iran's joining OECD and APEC will help to increase Iran's visibility in the international scientific collaboration network and reduce Iran's dependence on collaboration with the USA.

Considering the function of humanities and its comparison with other sciences, this research seeks to examine the scientific outputs and the weight of each, evaluation criteria and indicators, and the relationship between each output and criteria in the evaluation of these sciences Especially in language and literature. In terms of purpose, the research is applied, and in terms of the research implementation process, it is of a sequential and exploratory type. The steps of the work are as follows: 1. Identification and weighting of scientific outputs through the three steps of the library method, conducting interviews, and the Analytical Hierarchy Process (AHP); 2. Identifying the evaluation criteria of scientific outputs with the library method; and 3. determining priorities for evaluating scientific outputs through concurrent function deployment (CFD). Based on the findings, scientific outputs were divided into two categories: 1. Formats: scientific journal article, conference article, book, research project, and dissertation/thesis; 2. Activity: in policy-making, social (scientific-promotional), social (media), and economic contexts. Evaluation criteria are also divided into 8 categories: platform for creation, presentation and publication; writing structure; content; impact in online environment; scientific impact; social impact; economic impact; and cultural impact, each of which includes indicators. Finally, outputs and criteria have been prioritized according to three approaches and goals: production of science and promotion of knowledge foundations, applicability and responsiveness to society’s problems, literary creation/creative literature. Considering the importance and necessity of different evaluation of each field and discipline according to the nature of each one as an effective factor on the application and effectiveness of their scientific outputs, research policy makers can use a new approach in decision-making and establishing policies for evaluating the scientific outputs of the language and literature fields and humanities according to the results.

It is very difficult to predict stocks and commodity price index due to the presence of many and influential uncertainties. With the help of the accumulated information available in the current digital age and the power of high-performance computing machines, there is a lot of focus on designing algorithms that can learn stock market trends and successfully predict stock prices. Therefore, it will be very useful to create appropriate knowledge bases in order to increase the accuracy and efficiency of these systems and to facilitate the routine of using conventional knowledge in machine learning systems. The purpose of this research is to develop a Persian ontology for modeling the stock market and identifying factors affecting the stock market. The created ontology will lead to the enrichment and completion of the capacities of the existing knowledge bases in this field. For this purpose, in this research, a domain-specific ontology has been developed in the field of stock market and financial markets, which was prepared in Persian language by the authors of this research. After introducing this ontology, the details of the steps required to collect relevant data, semi-automated development and evaluation of this knowledge resource are described. The constructed ontology includes 565 concepts, 496 hierarchical relationships, 137 non-hierarchical relationships, and 937 samples that have been evaluated with various criteria and have a favorable status. It seems that this ontology in the current conditions and according to the evaluated volume and quality, is quite suitable to be used as a source of knowledge to improve the performance of machine learning systems for stock forecasting, and it can also be used to training stock market analysts and creating a knowledge base for brokerages, improving the process of retrieving semantic information and helping to determine the investment strategies of individuals in investment funds.

Following recent trends in information management systems, conventional word-based information retrieval methods are changing to concept-based approaches by means of the broad application of ontologies. More specifically, the use of ontologies for knowledge management is significant in the medical sciences and human disease domains due to the diversity and necessity of information sharing between numerous data repositories such as medical records, health record systems, and so on. Furthermore, ontologies make natural language processing approaches more feasible by reducing semantic ambiguity and making concepts comprehensible to computer-based deductions. In this research, a semi-automated approach for ontology development is proposed, which assists in identifying structural components of an ontology and determining possible relations between them based on scientific text records. The proposed approach, in a general view, includes the gathering of a large volume of technical data in text format, processing, and extraction of results with a minimal contribution of human-based supervision. The processing stage is coded in Matlab code named TmbOnt_Alfa and applies two main techniques including word frequency and Lexico-Synactic patterns analysis, to identify concepts and relations, respectively. The role of the human supervisor is narrowed to entering target terms, eliminating unnecessary outputs, and finalizing the ontology structure. In order to evaluate the efficiency of the proposed method, a case study for ontological development in the field of glaucoma has been conducted, and results are compared with medical subject headings of MESH descriptors, the Persian medical thesaurus, ontology of diseases, and Bioassay ontology (BAO).According to results, the developed ontology, when compared by Glaucoma entry, covered 80% of the medical titles in Mesh, 100% of the medical terms developed in the Persian Medical Thesaurus, and 100% of the Persian medical descriptors. Moreover, the resultant ontology structure is compatible with more than 90% of the same ontology represented in Bioassay and 57% of the ontology of diseases (DO). It also proposed an average of 30% more terms for existing ontological structures.

In order to provide comprehensive protection of personal data and data subjects, the General Data Protection Regulation (GDPR) has addressed various aspects. One of these protections is to pay attention to personal data that, due to their sensitive nature, need more protection (specific personal data). This regulation sets out various requirements for the processing of specific personal data. These requirements include the principle of prohibition of sensitive personal data processing unless there is a legal exception. Another requirement is the need for official authority oversight and legal authorization to process personal data relating to criminal convictions and offences. Determining a certain age for consent to processing is also a requirement for protecting children's personal data. In this study, by explaining in detail these requirements and clarifying how specific personal data is processed in EU law, the protection of specific personal data in Iranian law has also been examined. The conclusion is that although Iranian law on personal data does not have an independent law to rely on to protect specific personal data; However, according to the laws and regulations, legal doctrine, principles of Iranian law, there are many requirements for the processing of specific personal data set out in the GDPR, also in Iranian law.

One of the questions that institutions in the field of information technology are facing is how to get the services, products, equipment and materials they need? Relying on internal capabilities and resources (insourcing) or benefiting from external capabilities and resources (outsourcing) are the two main methods of acquiring services, products, equipment and materials needed by a business to achieve its goals. It is generally referred to as sourcing. Lack of financial resources and provision of expert human resources is one of the main issues of institutions in sourcing information technology systems, services and equipment, which has caused institutions to look for a pre-reliable and systematic procedure to choose between sourcing methods in response to this question. Based on this issue, this research aims to design an expert system for information technology sourcing decisions and apply it to the study of the Iranian Research Institute for Information Science and Technology (IranDoc) as a case. In order to achieve this goal, in the first step, 1- identifying the factors affecting the sourcing of information technology systems, services and equipment, and 2- designing an expert system for making information technology sourcing decisions. In this step, by using collection tools including library study and nominal group with experts and decision makers in the field of information technology in order to make a sourcing decision between the two options of external sourcing (outsourcing) and internal sourcing (insourcing), the legal and decision making framework in the form of a The expert system was designed and presented with tacit knowledge extraction, inference engine, comparison and prioritization structure, legal structure and execution process components. In the second step, in order to show the validity, the design and implementation of the prototype was considered as one of the validation methods. In this step, after designing the prototype, the decision-making process for 10 potential activities (projects) of IranDoc Information Technology Center was used. The results showed that the designed expert system meets the objectives of the research. The results of this research as a whole can provide a structured model for using the benefits of various sourcing mechanisms and reducing financial risks and providing human resources to the policy makers and managers and improve the current situation

AbstractThis study aimed to evaluate Philosophy Thesaurus of Research Center for Islamic Documents and Information Management according to ISO 25964 Standard (Part I & II) and also to examine the interoperability with other vocabulary control systems (ASFA Thesaurus and Persian Subject Headings). This research method was an applied survey in terms of purpose, and a survey-descriptive study in terms of data collection. The research population included the terms of Philosophy Thesaurus, which were selected 375 terms by using Morgan's table and random sampling method. The research population in the interoperability section was also the first six levels of the Philosophy Thesaurus with 85 terms. The tool and method of data collection was, respectively, a researcher-made checklist according to ISO 25964 standards and direct observation. The results showed that the compliance rate of ISO 25964 standard (part I) in the Philosophy Thesaurus is %75.52. The highest and lowest levels of compliance was related to the "software management" component (%79.34) and the "semantic relations" component (%66.66), respectively. The results of the interoperability of Philosophy Thesaurus with ASFA Thesaurus according to ISO 25964 standard (Part II) showed a %24.88 mapping, the highest of which was exact equivalence mapping (%49.41). Also, %42.47 of the terms has the possibility of automatic mapping. Interoperability with Persian Subject Headings was %89.41, the highest rate is related to exact equivalence mapping (%47.06). Also, %30 of the selected terms of the Philosophy Thesaurus can be automatically mapped with the terms of Persian Subject Headings. The interoperability in the thesaurus is an economical and efficient solution to save the high costs of producing and compiling and expanding the thesaurus. Also, paying attention to the rules of interoperability in accordance with the standards is the basis for data integration, and the user can achieve an efficient search with improvement precision and recall, regardless of the time, place, and type of database.

This study analyzes search stopping points and stopping rules used in the online information search process based on the concepts of Information Foraging Theory. The research method is a descriptive-analytical study. Sources are collected from various databases with no time restriction (before August 2022). The results show that from the perspective of Information Foraging Theory, in the online information search process, the searcher enters an information patch by issuing a query. Then searcher decides whether to stay or leave the information patch, by evaluating the relevance and irrelevance of information (scent-based stopping rules) and the time spent within and between patches (patch-based stopping rules). Each time the searcher leaves the information patch, he stops at a point and enters another information patch by issuing a query. The points of leaving one patch to entering another patch are temporary stopping points, because the search process continues and is not yet completed. Finally, by evaluating the information sufficiency (diet-based stopping rules), if searcher obtains enough information, he terminates the search session and stops at the permanent point. This study helps researchers to understand the different stopping rules at temporary and permanent stopping points. The implications of research are used in the design of information search behavior models.

The role of article publishing in academic and professional promotion is unprecedentedly increasing worldwide and researchers demand more transparency in the process of reviewing articles. Emergence of the Open Science movement led to the implementation of a new model of  peer review called "Open Peer Review"(OPR) in some journals. OPR is based on the values of "openness" and "transparency". The most obvious feature of OPR is reviewers’ open identity and open report. These characteristics have influenced the reviewers' behavior and the present study was conducted with the aim of identifying them.This study has been conducted in a Scope Review method based on the six-step framework by "Levace et al." and during it, after determining the purpose and questions of the research, 21 articles were selected, and the data were extracted, categorized and analyzed.The review revealed that, behaviors such as willingness to review, the review quality; time duration; bias towards issues such as gender, country, etc.; recommendation; the tone and volume of the review report, and requesting authors to cite their earlier works have been identified. "Quality", "recommendation", "bias", and "review time" were the most frequent behaviors studied, respectively. The identified behaviors were influenced by the characteristics of the open identity and open report. Eventually, OPR has been effective in increasing negative behaviors such as reducing the tendency to review, bias, asking authors for citing their works, and increasing the time of review. However, it has not had a negative effect on the review quality, the tone and volume of the review report, and, sometimes, it has improved them.

The volume of scientific documents and articles has increased dramatically in the last decade. It makes too difficult to find the relevant documents based on the user’s query. Information retrieval systems help researchers to find relevant scientific articles. One of the capabilities that help researchers to find the relevant papers is the feature of finding related scientific articles to an article. In other words, this feature allows to the researcher to view other related articles by selecting one article.The purpose of this research is to present a method based on the analysis of bibliographic references to identify related scientific articles in digital libraries. The statistical population of this research is the articles published in the last 5 years in Persian and English publications indexed in the ISC in the field of computer science. The proposed method is able to find the articles that are most similar to the given article by analyzing the references of the articles and ranking them based on their similarity. To do that, after extracting the title and obtaining the similarity between the existing references among the articles, those articles that have the most similarity are identified and sorted based on their similarity. The proposed method has been compared with other methods, and the obtained results on both Persian and English data are promising.

Nowadays, customers in any industry are not just looking for a product and expect to receive a personalized service based on their needs and create a different experience from the organization. From another point of view, the design of services according to the customer's needs will require a careful examination of the data related to the customer in different dimensions. Therefore, knowing the customer requires a systematic approach in order to identify the goals, influencing factors, algorithms and methods suitable for this field.

The upcoming research has analyzed the dimensions of customer recognition in the banking industry and its considerations with a data-oriented approach and the application of machine learning. The research method is applied according to the purpose and is meta-Synthesis according to the collection of information. To select the articles, 43 documents published in the period of 2016-2022 were identified as relevant and valid documents by searching in the reliable databases of Web of Science and Scopus, and further, with a meta- Synthesis approach, they were studied and coded.

The results of meta-synthesis led to the identification of three main categories: 1) Customer identification objectives understanding customer insight, identifying customer risk, organizational goals, determining customer lifetime value and product management 2) Customer identification factors: demographic, financial and behavioral and 3) machine learning algorithms: Probabilistic, Neural Networks, Ensemble, Regularization, Regression, Bayesian, Decision Tree, Dimensionality Reduction, Instanced Based and Clustering.

Based on the findings of the current research, according to the purpose of customer identification, available data and selected factors, basic and combined algorithms can be a way forward, but the important point is accurate data pre-processing. Another point is that no distinction has been made between real and legal customers, and most studies have focused on real customers, which can be attributed to the complexity of the chain of financial interactions of legal customers. Also, considering the banks' lack of emphasis on branches regarding the need to complete the information contained in the account opening forms or the lack of designing a suitable service to complete the information on electronic platforms, a more accurate understanding of the customer requires a review of these processes. It is worth mentioning that in none of the studies, customer recognition was done using only demographic factors, and depending on the purpose of the study, the factors were used in combination.