List of Articles Knowledge

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  1 - Model to improve banking by Using customer knowledge management and Mobile Banking and Its Impact on Customer Loyalty
  narges rezaei malek
  With progress of communication technology in the past two decades, use of ICT has become a success factor in the world of competition. To increase competition in the banking industry of Iran, many banks are willing to offer a unique service to their customers. Investmen More

  With progress of communication technology in the past two decades, use of ICT has become a success factor in the world of competition. To increase competition in the banking industry of Iran, many banks are willing to offer a unique service to their customers. Investment of private banks has concentrated on the presenting special services. That has led to more successful in attracting and retaining customers. To evaluate the influencing factors on banking services improvement, information technology and knowledge management as key factors were identified. This paper is to identify the most effective indicators to assess the impact of knowledge management and information technology for improving customer service of bank on customer satisfaction.180 experts of Bank Mellat is selected as population. Sample size was calculated by using a random sampling method. 130 samples were obtained but 120 questionnaires Were returned. Data were collected through questionnaires. In order to analyze the data from the structural equation modeling and LISREL software was used. In order to ensure the accuracy of the results and sensitivity analysis, regression analysis were applied. Finally, the results show that the customer knowledge management and mobile banking have positive effect on performance of banking service, and improving this kind of services have positive effects on customer satisfaction. Manuscript profile
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  2 - A Combinational Model for Evaluating Organizational Readiness for Data Warehouse Implementation by Using Analytical Hierarchical Process
  jafar bagherinejad zhinoos adibi
  Enterprise Data Warehouse initiative is a high investment project. The adoption of Data Warehouse will be significantly different depending upon the level of readiness of an organization. Before implementation of Data Warehouse system in a firm, it is necessary to evalu More

  Enterprise Data Warehouse initiative is a high investment project. The adoption of Data Warehouse will be significantly different depending upon the level of readiness of an organization. Before implementation of Data Warehouse system in a firm, it is necessary to evaluate the level of the readiness of firm. A successful Data Warehouse assessment model requires a deep understanding of opportunities, challenges and influential factors that a typical firm’s Data Warehouse (DW) may include. Actually, data warehouse system is one of Knowledge Management and Decision Support System tools. By this system, the distributed data throughout organizations could be collected, extracted and integrated and with knowledge discovery and data mining the latent data can be extracted and analyzed In this paper, after reviewing the relevant literature and a comparative analysis of assessment models for organizational readiness for implementation of Data warehouse system, a conceptual framework was designed and its validity was approved by test of hypothesis. Then, by using analytical hierarchical process technique and its expert choice software, criteria and sub-criteria of influential factors were assessed and weighted. The validity and effectiveness of the model including, six criteria and 23 sub-criteria with main influential factors named Information needs, Data structure , Organizational processes , Organizational factors ,Technical structure and Project management were approved by a field study and the relevant statistical analysis. Manuscript profile
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  3 - Provide a model of human resource knowledge architecture in knowledge-based organizations using a mixed approach
  abdollah saedi reza sepahvand najmoddin mosavi Mohammad hakkak
  20.1001.1.27170414.1398.11.39.4.0
  Knowledge architecture of human resources is more important than any other tool or element in the way of creating, organizing, storing, distributing and applying knowledge to achieve organizational goals. The present study was conducted to present the architectural mode More

  Knowledge architecture of human resources is more important than any other tool or element in the way of creating, organizing, storing, distributing and applying knowledge to achieve organizational goals. The present study was conducted to present the architectural model of human resource knowledge in knowledge-based organizations using a mixed approach. This research is based on mixed research and quantitatively and qualitatively, which is descriptive-survey in terms of purpose, application and nature and method. The statistical population of the present study consists of knowledge-based organizations in Lorestan province, 30 of whose experts have been selected based on the principle of theoretical adequacy and using purposive sampling. The data collection tool in the qualitative part of the research is a semi-structured interview and in the quantitative part is a questionnaire. In the qualitative section, data and information were identified using Atlas.ti software and analysis coding method and architectural indicators of human resource knowledge. In the quantitative part of the research, the final model of the research has been developed and presented using Matlab software and interpretive structural modeling method. The research results include the indicators and components of human resource knowledge architecture and the presentation of human resource knowledge architecture model in knowledge-based organizations. Thus, in addition to developing a human resource knowledge architecture architecture model, the findings indicate the identification of the main components of human resource knowledge architecture, knowledge management infrastructure, professional characteristics, situational characteristics and achievements of human resource knowledge architecture. Manuscript profile
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  4 - Survey on the Applications of the Graph Theory in the Information Retrieval
  Maryam Piroozmand Amir Hosein Keyhanipour Ali Moeini
  Due to its power in modeling complex relations between entities, graph theory has been widely used in dealing with real-world problems. On the other hand, information retrieval has emerged as one of the major problems in the area of algorithms and computation. As graph- More

  Due to its power in modeling complex relations between entities, graph theory has been widely used in dealing with real-world problems. On the other hand, information retrieval has emerged as one of the major problems in the area of algorithms and computation. As graph-based information retrieval algorithms have shown to be efficient and effective, this paper aims to provide an analytical review of these algorithms and propose a categorization of them. Briefly speaking, graph-based information retrieval algorithms might be divided into three major classes: the first category includes those algorithms which use a graph representation of the corresponding dataset within the information retrieval process. The second category contains semantic retrieval algorithms which utilize the graph theory. The third category is associated with the application of the graph theory in the learning to rank problem. The set of reviewed research works is analyzed based on both the frequency as well as the publication time. As an interesting finding of this review is that the third category is a relatively hot research topic in which a limited number of recent research works are conducted. Manuscript profile
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  5 - Improving Opinion Aspect Extraction Using Domain Knowledge and Term Graph
  Mohammadreza Shams Ahmad  Baraani Mahdi Hashemi
  20.1001.1.27170411.1402.15.55.1.2
  With the advancement of technology, analyzing and assessing user opinions, as well as determining the user's attitude toward various aspects, have become a challenging and crucial issue. Opinion mining is the process of recognizing people’s attitudes from textual commen More

  With the advancement of technology, analyzing and assessing user opinions, as well as determining the user's attitude toward various aspects, have become a challenging and crucial issue. Opinion mining is the process of recognizing people’s attitudes from textual comments at three different levels: document-level, sentence-level, and aspect-level. Aspect-based Opinion mining analyzes people’s viewpoints on various aspects of a subject. The most important subtask of aspect-based opinion mining is aspect extraction, which is addressed in this paper. Most previous methods suggest a solution that requires labeled data or extensive language resources to extract aspects from the corpus, which can be time consuming and costly to prepare. In this paper, we propose an unsupervised approach for aspect extraction that uses topic modeling and the Word2vec technique to integrate semantic information and domain knowledge based on term graph. The evaluation results show that the proposed method not only outperforms previous methods in terms of aspect extraction accuracy, but also automates all steps and thus eliminates the need for user intervention. Furthermore, because it is not reliant on language resources, it can be used in a wide range of languages. Manuscript profile
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  6 - Survey on the Applications of the Graph Theory in the Information Retrieval
  Maryam Piroozmand Amir Hosein Keyhanipour Ali Moeini
  Due to its power in modeling complex relations between entities, graph theory has been widely used in dealing with real-world problems. On the other hand, information retrieval has emerged as one of the major problems in the area of algorithms and computation. As graph- More

  Due to its power in modeling complex relations between entities, graph theory has been widely used in dealing with real-world problems. On the other hand, information retrieval has emerged as one of the major problems in the area of algorithms and computation. As graph-based information retrieval algorithms have shown to be efficient and effective, this paper aims to provide an analytical review of these algorithms and propose a categorization of them. Briefly speaking, graph-based information retrieval algorithms might be divided into three major classes: the first category includes those algorithms which use a graph representation of the corresponding dataset within the information retrieval process. The second category contains semantic retrieval algorithms which utilize the graph theory. The third category is associated with the application of the graph theory in the learning to rank problem. The set of reviewed research works is analyzed based on both the frequency as well as the publication time. As an interesting finding of this review is that the third category is a relatively hot research topic in which a limited number of recent research works are conducted. Manuscript profile