پژوهشنامه پردازش و مدیریت اطلاعات
سال سی و هفتم شماره 1 (پیاپی 107، پاییز 1400)

Today, information technology as a science, affects almost all components of societies, so that it is used by organizations to improve organizational processes and gain a competitive advantage due to the complexity and competitiveness of the business environment. Due to the importance of this issue in this study, the components of information and communication technology in evaluating of the performance of human resource management in service companies have been studied. For this purpose, a questionnaire including six dimensions of communication and information technology was designed and distributed among a statistical sample of 50 managers of service companies. The validity of the questionnaire was evaluated using Lavache validity method and based on the opinion of experts, and finally the research hypotheses were analyzed using SPSS software. According to the normality test, it was shown that the views of the statistical sample were not normal and the non-parametric Spearman coefficient test method examined the correlation of ICT components. Finally, the results showed that correlation exists between web services, cloud information processing, artificial intelligence, mobile communication technology, smart business information, and ICT of human resource management of service organizations, so the development of mobile and web applications, which has recently been introduced, offers a new model of intelligence to the organization and there is potential for business improvement in bringing a great benefit to the organization.

Today, despite many benefits of cloud computing technology, including cost savings, agility, increased flexibility and scalability the issue of information security is the main obstacle to the tendency of organizations towards cloud computing. In addition to infrastructure issues and political factors in Iran, there are many security risks in cloud computing technology. Therefore, the purpose of this study is to extract and rank these security risks. In this regard, by studying the theoretical foundations related to the research topic, these factors are extracted and categorized according to the opinion of experts, and then by designing questionnaires of different pairwise comparisons, collecting comments and combining different weighting methods based on pairwise comparisons by Copeland aggregation method, security risks were ranked. In this ranking, data privacy risk was the first priority of cloud computing security risks.

In recent years, the number of articles studying the Internet of Things technology in supply chain management and logistic has grown rapidly. The purpose of this paper is analyzing the studies that have been done in this area by reviewing the relevant literature and while identifying the existing theoretical gaps, introduces future research opportunities. This paper collects and analyzes information using a systematic literature review methodology and paradigm funnel approach. Systematic literature review is a methodology reliable and recommended by a large number of scientific papers. However, selection of certain criteria for inclusion and exclusion of papers introduces publication bias, which should be considered an intrinsic limitation to systematic literature review. Numerous studies have been conducted in the area of Internet of Things and supply chain management, but there is no synthesis of the knowledge that would allow one to draw conclusions regarding the evolving nature Internet of Things in supply chain management and to extend the theories in this area. This paper will address that gap, applying the paradigm funnel technique. For this purpose, Scopus, Science Direct, Emerald and Francis & Taylor databases were searched and a total of 209 articles were retrieved. After initial screening, 105 articles were excluded due to inconsistency with inclusion criteria and after qualitative screening, a total of 36 studies were selected for analysis. The selected 36 articles focus mainly on level 2 and 3 of the paradigm funnel. Only two articles were placed in the first level of the paradigm funnel and no studies in the level of deep hypotheses (fourth level) were observed. Most studies used qualitative methods to collect and analyze data. Also, the findings show that future researches can use empirical observations and data generation to further exploration of internet of things in supply chain management and logistic.

The purpose of this research is to design and develop an integrated open portal for searching and retrieving information of institutional repositories of universities, and higher education and research institutes in Iran. This paper discusses the collection and aggregative infrastructures, conceptual model, and architectural design and components that a practical institutional repository search portal should have. Iranian Institutional Repositories Integrated Search (IRIS) Portal architecture and services are designed as the first such example in the country. A functional development of this portal will be provided as a local system after implementation.In the process of designing and developing IRIS based on some background knowledge expanded after reviewing and collecting information of scientific texts and their methodologies, needs and feasibility assessment of existing infrastructure at the national level, analyzing similar international systems, the initial product implementation plan called “Design and Development of Iranian Institutional Repositories Integrated Search (IRIS) Portal” were targeted along with all the details of the subsystems and related workflows. In the system development process of this research, in five stages Scrum agile framework was used as an iterative and incremental methodology to control IRIS software project management.For designing and developing of this system, we reviewed similar models used in other countries. The general architecture of this system is based on the data provider and service provider model using the OAI standard. In the architecture of this system, three major parts of data mining system, data processing management system and entities linking, and finally the provision system were considered. In the design of IRIS system, features such as ease of use (user friendliness), customizable and extensible web user interface (especially with common languages), high visibility by search engine and indexing tools, permanent access to resources, support for search logic and a unique identifier for each document were considered. What is very important in the development of this system is the need to publish data freely and under open and permanent source licenses. Otherwise, one cannot expect the development of a suitable system that can mine, collect and aggregate data in an integrated manner. After implementing the system, it was found that the data entered in the data providers in this model, mainly had structural problems, and eventually the IRIS service may encounter some defects. It seems that by preparing policies by the Ministry of Science, Research and Technology (MSRT), it is possible to ensure the regular updating and loading of data in organizational repositories and finally the IRIS system.

Information security is one of the effective factors in protecting and using digital libraries which can help improve the status of these libraries.This research reviews the accessibility to information security of digital libraries in digital libraries of Qom city. In this study, definitions of digital libraries include libraries based on their mission and using experts, organize digital documents and provide them to members in the form of information services.This study is a survey and research community was both public and academic digital libraries (including 5 libraries) in Qom city. Data collection tool is a questionnaire based on the standard ISO/ IEC 27002 which is an information security standard developed by the international organization for standardization (ISO) and International Electrotechnical Commission (IEC).The results of this study indicate that the average information security among digital libraries in Qom city is estimated to be 0.801, which considering the research evaluation method, it can be said that it has a strong level of information security. The development of information systems to provide effective services in digital libraries has played an effective role .There is also a significant relationship between different indicators of information security in digital libraries of Qom city. Weaknesses and strengths of digital libraries in Qom city, respectively, include physical and environmental security as a weakness and business continuity management has been introduced as a strength. Utilizing passive defense, participation of security groups to prevent hackers, identifying security gaps, training specialized forces and having an executive plan for information security are among the suggestions of this research. Finally, it must be stated that information security is at a high level in libraries in Qom city.

It is necessary to pay attention to the dimensions of interaction as a basic concept in computer environments to understand and draw the psychological function and users’ behaviors and the optimal design of Interactive Information Retrieval systems. Also the issue of interaction, due to its complex nature, requires the simultaneous attention of personal-cognitive, behavioral, environmental factors of users related to the process of information retrieval and correct understanding of these components. Hence, the main aim of this study is presenting a framework for main and sub elements of information retrieval interaction based on social-cognitive theory and to develop a checklist for Interactive Information Retrieval based on this theory in digital libraries. The present study was conducted using library and survey methods. In this regard the survey of experts and Delphi panels were used in two stages. Initially, the extraction and evaluation of various components of Interactive Information Retrieval in digital library systems as well as the effective components of social-cognitive theory were done via the study of different texts. Then, the dimensions and components of interaction, based on social-cognitive theory were calculated using academic experts’ opinions. These elements were set and validated in a five-option Likert scale questionnaire. The main components include three dimensions of interaction with information, interaction with interface and interaction with tasks and sub-components, each of which forms the effect group and social-cognitive theory with the three main components of personality, environment and behavior form the causes group. The community of experts included 17 experts in the field of information retrieval based on the snowball sampling method. Considering the high values of Kendall consensus coefficient in two components of personality and behavior of about 0.77 and the coefficient of 0.72 in the environment component, a total of 60 components in these three dimensions were agreed. Based on the research findings and in addition to the two stages of Delphi and after removing the components with an average of less than three in the Likert scale, 21 components in the personal dimension, 20 components in the behavior dimension and 19 components in the environment dimension were approved by the research experts. The results indicated that the authenticity item of all three components of personality, behavior and environment and comprehensiveness, objective work task complexity items of environment and subjective work task difficulity item of behavior dimension were recognized as unimportant items according to the opinion of research experts and were eliminated. The framework obtained from this study can be used as the basis for future research to apply these components with emphasis on three basic aspects of user behavior in the optimal design of Interactive Information Retrieval systems.

The process of information seeking and retrieval is a very complex cognitive process. One of the important approaches to exploring and understanding this process is to examine the user’s experiences. The purpose of this study was to concept and understand the Ph.D. students’ experience of the phenomenon of information seeking and retrieval in their research process.The approach of this study was interpretative that was carried out through qualitative phenomenographical research method. The participants in this study were Ph.D. students in different fields at Ferdowsi University of Mashhad in 2019. Sampling was purposeful, criterion and snowball. The maximum diversity was considered in the sample selection and was continued to the theoretical saturation of data. Semi-structured interviews were conducted with 20 students. Interviews were implemented and analyzed through an inductive and theoretical coding method using MAQDA12 software.The results showed that after analyzing the data gathered from the interviews, six descriptive categories emerged about how Ph.D. students perceived and experienced the information seeking and retrieval phenomenon. Six categories were information seeking and retrieval as an endless sea, a valuable treasure, a road full of lights, the key to rescuing, eating the desired fruit, and a bridge to reach knowledge. The results showed that the Ph.D. students described the information seeking and retrieval in their research process as important and necessary and that their main problem was learning and teaching which made them feel unpleasant.Although this qualitative study does not aim to generalize the findings, however, according to the findings of the present research at the outcome space, this type of students’ perception and description of information seeking and retrieval phenomena at the highest academic degree is an alarm for the higher education system and should be taken seriously into consideration.

Keywords and key phrases are subsets of most relevant words or phrases that summarize contents of a document while they play a critical role in information and document retrieval. Keyword extraction from scientific text is challenging and time-consuming due to the technical and multi-subject nature of the text, while the number of documents requiring keywords is increasing. There are various algorithms and methods developed for automatic keyword extraction. Rapid Automatic Keyword Extraction (RAKE) is a popular algorithm in this domain. RAKE’s decisions are based on the observation that keywords generally contain multiple words and they rarely include stopwords and words with minimum lexical meanings. Candidate keywords are a set of single-word or multi-word sequences selected based on the scores assigned to them by some scoring criteria in RAKE.In this research, a new modified version of RAKE algorithm is proposed in which candidate keyword scoring scheme is improved to increase precision and recall in the keyword extraction process. The proposed algorithm is to cover some of the main weaknesses of RAKE algorithm, especially in Persian scientific documents. To study the weaknesses of RAKE algorithm and evaluating the proposed modified version of RAKE, a set of metadata of Persian theses and dissertations are used. The result of test and evaluation of the proposed algorithm confirm improvement in precision, recall and F-measure.We study effectiveness of RAKE in extracting keywords from Persian texts. We find that RAKE algorithm often extracts long phrases with redundant words on Persian texts, leading to low accuracy. In this paper, we study sources of scoring inefficiency of RAKE algorithm and propose an improved version of RAKE algorithm with a novel scoring mechanism. Our scoring mechanism overcomes some of the weaknesses in RAKE’s original scoring for Persian texts and yields better results. Our evaluations on Persian corpus demonstrate that our improved RAKE algorithm outperforms original RAKE algorithm by extracting more accurate keyword. Our results show that improved RAKE achieves more than 20% higher precision and recall on average compared to original RAKE.

The purpose of this article is to present a plan to create coherence between thesauruses and specialized vocabulary compiled in IranDoc in the form of a meta-thesaurus. A meta-thesaurus is a cohesive combination of structured or controlled languages or compiled thesauruses and document lists that are obtained by linking, merging, and combining them. In this mechanism, in order to integrate the developed thesauri, each concept in a thesaurus is linked to the closest equivalent concept in other thesauri with the help of markers. In the process of communication between concepts, it is possible to translate the user query in the form of a systematic and comprehensive search of databases organized by various thesauruses and provides a platform for increasing comprehensiveness in information retrieval. In IranDoc, specialized thesauruses have been compiled in the 2001-2010 and updated in the years 2017-18. In addition, a collection of specialized dictionaries and vocabularies have been compiled and published. It is necessary to combine these words and thesauruses with each other in order to prevent the false loss of information in the search of Iran›s scientific database (Ganj) and to provide targeted access to specialized information. This article examines and analyzes various sources in the formation of meta-thesaurus in identifying related concepts, expressing the application and also the steps of its compilation.

In designing search engines, it is important to check the database you are studying and make a connection with it.This study is an applied one conducted by using observation method. What is used in this study is a case study.The pattern of most searches is generally partial and specific in most cases. Participants begin their search with general information such as introducing and reviewing facts, and then focusing on specific aspects. In some cases, users come up with new ideas while searching. According to the results, general background, subject knowledge, time range and tools available influence desired response.According to the analysis of findings and results, it is suggested that information behavior using neural network is more accurate in identifying information skills, barriers, goals and motivation and determining and predicting resources and services. Information and ways of accessing information should be compared with the results of present study. Based on the results, it seems that specialized information retrieval training for all classes of users is needed to increase information skills of current and future users.Current search engines retrieve only part of relevant documents in a collection. Better models are needed to overcome the huge volume of documents. The proposed model in this way enables improved data retrieval in a short period of time. It is also possible that search model is also updated each time with user searches and results in more accurate results.

In recent years, knowledge management has become a fundamental principle in the field of management. Since the introduction of knowledge management, many institutions have tried to measure the benefits of using this concept. Success in implementing knowledge management and continuing its usage largely depends on measuring knowledge management benefits. However, few studies were conducted on this issue. This study, by using the adaptive neural fuzzy inference method (ANFIS) via Matlab 2017 software, tried to provide a predictive model to measure the benefits of knowledge management in the organization. The study population consists of scientists and experts working in 15 branches of the Social Security Organization, with a minimum of five years of experience in knowledge management related tasks. Based on the results, the degree of compatibility of the estimates with the actual results and the predictability and accuracy of the results were discussed, and at the end, based on the results, guidelines were provided to the studied organization.

This study aimed to identify the main features of Open Access tweeted by Twitter users and to analyze their opinions about them. A sample of English tweets about Open Access was identified and analyzed using a quantitative content analysis method with opinion mining approach. To do so, based on a wide literature review, the main features of Open Access discussed in the literature were identified and used to compose the search formula. This step retrieved 874270 tweets. The data were, then, cleaned using exact match search in Excel, resulting in a sample consisting of 165320 relevant tweets. The sample was, then, classified into four thematic groups including “costs and financial resources”, “publication and resources”, “models” and “validity and quality”. To analyze the tweets’ contents and calculate their opinion scores, the KNIME and SentiStrength applications were used, respectively. The data were analyzed using descriptive and inferential statistics in Excel and SPSS. The results showed that the concepts related to the Open Access “publication and resources” have been tweeted the most. The group being set aside given its all-inclusive nature, the “credibility and quality” as well as the “costs and financial resources” are the two main issues discussed by Twitter users. According to the opinion mining results, more than half of the tweets were neutral and the positive opinions are of slightly higher frequency compared to the negative ones. The “credibility and quality” and the “costs and financial resources” received more negative tweets. Thus, in line with previous surveys conducted to explore the concerns of researchers and stakeholders about Open Access, the present study provided an almost similar picture for the social space. Since Open Access to scientific information is a necessity for the development of knowledge-based societies, the results highlight the need to take serious steps to strengthen its positive points and devise solutions to the problems and challenges leading to the negative feedbacks.