پژوهشنامه پردازش و مدیریت اطلاعات
سال سی و هفتم شماره 4 (پیاپی 110، تابستان 1401)

The continuation of comprehensive developments in the future and their impact on various scientific fields, reveals the need for systematic studies on future knowledge. One of the most important aspects of the field of knowledge and information science from future developments that clarifies the need for future research in this field is the study of research topics. In this regard, the present study seeks to forecast the thematic trend of future research in this field in Iran by 1409. This research is of applied type and has been done with text analysis and deep learning approach. After pre-processing and thematic classification of research, deep neural network algorithms have been used to model past research and Forecast future topics. The study population includes articles extracted from the website of Iranian publications indexed in the ISC database during the years 1972-2019 and articles conducted in Iran that have been indexed in the Web of Science website from 1945-2019. All research processes are implemented in the Python programming language. The research findings showed that in the future, the highest number of researches will be in the fields of Internet and web studies, respectively; knowledge management; Information and Communications Technology; And scientometrics and informatics will be allocated. In addition, in the next decade, the growth trend of research in the field of Internet and web studies; Scientific and information communications; Librarians and information specialists; Data mining and knowledge discovery; Artificial intelligence and future studies will be faster. Areas such as organizational management, theoretical foundations, information resource management, and information processing and management will also have fewer fans among future researchers, and in addition, in the future, the axes of organizational management; Libraries and information centers and archives; Information resource management; Information and digital literacy; And the organization of information and knowledge will experience a slower growth process. The results show that the issues that have been raised in this field in the past years, despite the changes they have had, will continue to live in the same way in the future and only the context, format, methodology and method of their implementation will change. In other words, due to the transfer of traditional functions of this field to the digital and virtual world and increasing the role of information technologies, communication tools, Internet and web development, semantic tools and intelligent technologies in providing services and different dimensions of this field, future research topics They will be affected by these developments and will move towards web-based topics based on new technologies.

The purpose of this study is to identify situations that require information system support to user search tactics and presenting a model. The method of the present study is a combined approach that has been collected based on quantitative and qualitative data. The data taken from the questionnaire constitute quantitative data and the information obtained from the ambitious protocol derived from the software. The research sample is 35 graduate students (PhD students and undergraduate and graduate students) from the two fields of humanities, engineering in Tehran. A 17-item questionnaire was used to gauge users' judgments about the importance of effective components in supporting the information system from the use of search tactics. Also, 4 search tasks based on Maxwell and Anderson classification based on cognitive perspective were provided to the searchers in order to perform the search. The information obtained from morae software, which included data obtained from the thinking protocol and search observations, was identified to identify situations in need of extraction support, and the main and sub-categories were determined based on interview-based information to improve the search to support the information system. Finally, a conceptual model of the research is presented.Given the limited studies in the field of information system support for the use of search tactics, the findings of this study help to clarify what happens in the search process and situations that require user support from the information system and provide information for database designers.

This research evaluates the maturity of information technology governance based on the COBIT 5 framework in the National Library and Archives of Iran. The research methodology is based on the COBIT 5 maturity model that measures the capability of IT processes using the ISO / IEC 15504 standard. According to this standard, the capability of each process is evaluated on a scale of 0 to 5 to determine its maturity level. The data were gathered using the COBIT 5 check lists in 5 process areas for 37 IT processes with the help of NLAI managers responsible for each field (based on the COBIT 5 RACI chart). After analyzing the general and specialized indicators of each process, the maturity ranking, maturity level mean and maturity gap were determined in each domain. The results showed that the maturity level achieved in five process areas (1-IT governance processes: Ecaluate, Direct and Monitor; 2-Align, Plan and organize, 3-Build, Acquire and Implement; 4-Deliver, Service and Support; and 5-Monitor, Evaluate and Assess) are not in line with the strategies of the National Library and Archives of Iran, the overall average of maturity level of 37 evaluated processess is 0.81 out of 5, and this organization has a gap of 4.9 to the optimal level.

As a growing issue, there is no formal, universally accepted definition of the Internet of Things. Browsing the literature  in this area, one finds that  that every single researcher and organization has interpreted this technology as they understand it. As a result, 116 various definitions of this emerging technology have been proposed so far. This research  is an attempt to better understand and master the definition of the Internet of Things; the research is carried out through the method of browsing the literature and reviewing the relevant texts. All relevant but varied definitions and descriptions have been exhaustively to provide a definition that could be used as a reference for the stakeholders who want to understand the concept of the Internet of Things. An examination of the definitions provided in this area showed that many of them have  common similarities. In this article, a comprehensive definition of the Internet of Things derived from the scientific definitions available in articles, books, and websites of various global organizations is provided. Finally, the authors provide a fairly comprehensive definition of the Internet of Things that is not an absolute definition of the true meaning of the term in question, but is expected as part of its research and development for a clearer meaning of the term. This study provides a comprehensive overview of the definitions offered in the scope of the Internet of Things and can be useful for those who are new to the Internet of Things or researchers who want to delve deeper into the field.

Given that television is one of the most influential media that uses written language in various TV programs, like advertisements and subtitles, it can be considered as one of the best tools for expanding and teaching the orthography approved by Persian Academy of Language and Literature. In this regard, the present study addresses the representation of Persian orthography in the national media and its compliance with the guidelines approved by the Academy. In this research, an extension of TOPSIS method has been used in the framework of Multiple Attribute Decision Making. To this aim, orthographic content of seven IRIB TV channels namely, One, Two, Three, Four, iFilm, Tamasha and News were analyzed. Then, the compliance rate of each was verified by the “Guidelines on Persian Orthography” approved by the Academy and the channels were ranked by linear assessment method. Findings indicate that none of the seven channels are fully compliant with the guidelines.

The number of libraries utilizing smart computers and software to provide different services is unprecedentedly increasing worldwide. Librarians and informants have also attempted to use AI technologies such as expert systems, chatbots, and other smart services to improve and upgrade the quality and quantity of services. Therefore, the present study focused on identifying and introducing the capabilities and applications of expert systems and chatbots for library services.

This study has been conducted in a systematic review method with a seven-step process by Wright et al. These steps in the systematic method are: determining the research question and then the protocol or contract for performing the task, searching for texts, extracting data, evaluating quality, analyzing data and presenting the results, and finally, interpreting the results. Then keywords in this field were searched in international (i.e., Web of Science, Scopus, and Google Scholar) and domestic (i.e., Magiran, Scientific Information Database/SID, and CIVILICA) databases regardless of the time interval. Finally, 34 articles were selected.

The review of 34 related studies revealed that expert systems are used as technical, general, and managerial services in libraries. However, due to the nature of chatbots that are used for smart conversations and communications as human interactions, various studies have so far identified and introduced the applications of these chatbots only in the general services section of libraries while in reference services and interviews in particular.

Eventually, librarians are expected to become familiar with the capabilities and applications of expert systems and chatbots, as well as participating in the design and application phase of expert systems for libraries. It is further suggested that further studies investigate the role and application of chatbots in the technical and managerial services of libraries to provide a basis for designing these intelligent systems for all library services.

Organizations produce massive volumes of variant and valuable data on a daily basis. Identifying the risks of using and processing organizational big data and finding solutions to manage and reduce these risks, paves the way for organizations to succeed and gain a competitive advantage. On the other hand, in organizations, due to the dynamics of the business environment, the factors affecting the reduction of risks affect each other, and a change in the status of one factor will directly or indirectly affect other factors. For this purpose, by reviewing the thematic literature and the opinions of experts, a framework consisting of four influential areas and 44 effective factors was formed. According to the qualitative nature of the influencing factors, fuzzy concepts have been used for modeling and analysis. Furthermore, to model the relationships between factors and determine the most effective and influential factor in organizations, the FUZZY DEMATEL technique has been used. In this article, the modelling is based on the opinion of experts and subsequently, the results of modeling and calculations have been evaluated with the opinion of experts. By using the achievements and modelling methods mentioned in this research and according to the needs of the organization, they can model and plan to minimize the risks of using their organizational big data as much as possible.

Since 2001s (1380s according to the Iran’s solar calendar), the increasing rate of writing and publishing scientific articles in Iran has become very intense. This caused in addition to the governmental organizations, such as Irandoc & the National Library and Archives of the Islamic Republic of Iran, numerous other online systems, such as the General Portal of Humanities, Noormags, Magiran, Elmnet, Civilica, etc, to manage knowledge and to provide structured archives of the scientific documents. Each of these archives provides facilities to the user. One of these facilities is searching on the documents. An accurate search can greatly improve the usage of these online systems. To increase the accuracy of the search result, it is necessary to determine the scientific field of articles. Classifying large volumes of scientific resources in different fields is very time-consuming. Using machinery methods can be a solution to reduce the severity of the task.The main contribution of this paper is to provide a classification model to classify Persian scientific articles. Although in previous studies, the classification task has been mainly used for simple texts, in this study, the neural network-based classification models, such as convolutional and perceptron neural networks, are used with the contextualized semantic representation, such as ParsBERT; and the results are compared with the other common method utilized for vectorization, namely Word2Vec. To this end, we use the data from the General Portal of Humanities, which includes various articles in the Humanities and each article contains the label of the field. One of the neural network characteristics is that a set of hidden features from the data in the vector space is created and used to train the model. According to the experimental results, the Perceptron classifier that utilized ParsBERT representation obtained the highest performance which is 74.71% based on the Micro F-score, and 72.55% based on the Macro F-score.

Human users can easily divide a bibliographic reference to its constructing fields such as authors, title, journal, year, etc. However, due to the variations in formats and errors made by the authors in citing documents, it is difficult to automate this task. There exist many solutions for this problem, known as citation parsing problem in the literature, however, none of them is compatible with Persian language. This is mainly due to high language-sensitivity of these solutions. Considering the important role of citation parsing in tasks such as autonomous citation indexing and information retrieval, in this paper, we propose an intelligent method for citation parsing in Persian language. The proposed method uses the support vector machine (SVM) classification method as its core. The results of testing the proposed method using a dataset designed for this task show 95% in average for precision, recall and F1 measures for extracting different fields from a bibliographic reference, which is quite plausible.

At present, most of the daily shopping of people is done through systems and online stores; therefore, providing a model for evaluating systems and online stores in order to boost the business market and the competitive environment between systems and online stores will be very important. The main purpose of this study is to provide a model for evaluating these systems. Initially, resources related to the evaluation of online store websites and the models used for them were collected and reviewed; then, using qualitative content analysis, the concepts available in online store websites were extracted and categorized into thematic items; finally, the obtained themes were adapted to the main dimensions of Delon and McLean model. Lavshi content validity method was used to confirm the validity of the evaluation model and Cronbach's alpha coefficient was used for reliability. According to the five main dimensions of Delon and McLean model, the evaluation model of systems and online stores was presented in 44 appropriate items. In terms of system quality, 7 items, information quality, 11 items, service quality, 18 items, user use and satisfaction, 6 items, and personal effects, 2 items were approved. Given that the creation and use of online stores in Iran is still young and online shopping through the website of online stores is constantly expanding, the items obtained in this study in the form of Delon and McLain model are among the key indicators. Are considered necessary to improve service delivery and business prosperity and need to be considered by designers and their stakeholders; Therefore, it is very important to use all the appropriate and accepted items in the model of this research. In general, by reviewing the obtained items, it seems that in addition to ensuring the credibility of the online store to buy from it, it is very important to pay attention to the user interface and customer relationship management system; In addition, many items such as the existence of search tools, proper categorization of goods in order to facilitate customer interaction with the system and the online store indirectly indicate the importance of the user interface.

Several factors are involved in the production and presentation of recommender systems.The aim of this study was to investigate the effect of the two challenges lack and sparsity of data on the effectiveness of the proposed results of the RICeST Journal Finder. The corpus includes more than 15,000 articles from technical and engineering publications in the period 2013 to 2017, which have been collected from their website. Textual elements of these articles were extracted, normalized and processed, and a research body database was created. Based on the number of collected articles, by using Cochran's formula, 400 basic articles that previously published in related to the topic of each journal were selected in a random-proportional method. Title and abstract of these articles as a query, in order to receive the system Journals suggested, to print the article in two stages of before and after improving the two challenges of lack and sparsity of data in the test corpus. The suggested results in each step were saved in Excel. Finally, the effectiveness of the system results in each stage was determined by Leave-one-out Cross-Validation method and based on the accuracy criterion in k.The relative abundance of categories showed that, in the current situation, the target journal was suggested in only 26% of searches in the first 3 ranks. After enriching, normalizing and processing the data and thus improving the lack of data challenge, although 30% of the results were still rated above 10; But the accuracy of the results in the first 3 ranks increased by 15%. Also, after thematically categorizing the data with the aim of improving the sparsity challenge, 30% increase in the accuracy of the system results in the first 3 ranks compared to the previous step was achieved. The results of this study showed that enriching the database, improving the processing process and thematic classification of data in RICeST journal finder can reduce the two challengs lack and sparsity of data and increase the effectiveness of the proposed results of this systems.

Students’ growth and development have always been considered important by the education system as they are the future assets of their country. Although many students can flourish their talents and creativity, we are faced with a large number of students each year whose talents are squandered leading them to a position far from success. Today, with the more students entering in different academic levels and the variety of study disciplines, the necessity to properly guide students is felt more than ever. For this purpose, educational data mining has received special attention from the educational system’s officials in recent years. So far, various classification methods and techniques in data mining and machine learning have been used to predict student performance. However, these individual classifiers have limitations such as complexity and instability for predicting performance in the education process. To tackle this problem, ensemble classification has been proposed as a new and efficient method. Ensemble classification systems combine the results of several individual classifiers to provide a model with better performance. In this paper, a new Ensemble classification system is presented using multilayer neural networks and SOM clustering in order to estimate and classify the grade point average of undergraduate students. In addition, we used averaging and majority voting as combination methods for aggregating the results of individual classifiers. Evaluation results on real university data show that our proposed ensemble system provides better accuracy and performance compared to prevalent individual classification methods. Also, the proposed ensemble system obviously outperforms other popular ensemble methods in classifying students’ GPA.