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Soheila Sardar

Bio: Soheila Sardar is an academic researcher from Islamic Azad University. The author has contributed to research in topics: Customer retention & Loyalty. The author has an hindex of 3, co-authored 6 publications receiving 41 citations. Previous affiliations of Soheila Sardar include Islamic Azad University North Tehran Branch.

Papers
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Journal ArticleDOI
TL;DR: Simulation results over four social network databases from Facebook, Google+, Twitter and YouTube demonstrate the efficiency of the proposed KFCFA algorithm to minimize the information loss of the published data and graph, while satisfying K-anonymity, L-diversity and T-closeness conditions.
Abstract: In recent years, an explosive growth of social networks has been made publicly available for understanding the behavior of users and data mining purposes. The main challenge in sharing the social network databases is protecting public released data from individual identification. The most common privacy preserving technique is anonymizing data by removing or changing some information, while the anonymized data should retain as much information as possible of the original data. K-anonymity and its extensions (e.g., L-diversity and T-closeness) have widely been used for data anonymization. The main drawback of the existing anonymity techniques is the lack of protection against attribute/link disclosure and similarity attacks. Moreover, they suffer from high amount of information loss in the released database. In order to overcome these drawbacks, this paper proposes a combined anonymizing algorithm based on K-member Fuzzy Clustering and Firefly Algorithm (KFCFA) to protect the anonymized database against identity disclosure, attribute disclosure, link disclosure, and similarity attacks, and significantly minimize the information loss. In KFCFA, at first, a modified K-member version of fuzzy c-means is utilized to create balanced clusters with at least K members in each cluster. Then, firefly algorithm is performed for further optimizing the primary clusters and anonymizing the network graph and data. To achieve this purpose, a constrained multi-objective function is introduced to simultaneously minimize the clustering error rate and the generated information loss, while satisfying the defined anonymity constraints. The proposed methodology can be utilized for both network graph structures and micro data. Simulation results over four social network databases from Facebook, Google+, Twitter and YouTube demonstrate the efficiency of the proposed KFCFA algorithm to minimize the information loss of the published data and graph, while satisfying K-anonymity, L-diversity and T-closeness conditions.

42 citations

Journal ArticleDOI
TL;DR: Results indicate that quality has the highest priority and that production technology has the lowest priority among ten factors for oil project selection, thus reflecting the impact of US sanctions on oil production in Iran.

36 citations

Journal Article
TL;DR: In this paper, the authors used the five dimensions as following, ideal selfconcept, fit lifestyle, quality of service, employee behavior and brand awareness for measuring brand equity in the study and also colleagues (2011) were taken into consideration.
Abstract: IntroductionThe service sector has enjoyed considerable growth in recent years, so that the highest share of gross national product GNP in developed countries is related to the services sector. In Iran, the current share of the service sector in the economy is 48 percent, and over ten million people are employed in this sector (Jalali, Khairi, and Khadem, 1390). The researchers believe that as some inherent characteristics of services, such as being intangible, variability, inseparability and mortality, the concept of branding in marketing services is much more important than physical goods because it had changed the virtual nature of services and presented this nature more truly and more tangible. A powerful brand increases the trust and the power of customers in visualizing and a better understanding of the characteristics of intangible services (Hosseini et al., 1393). On the other hand, many organizations (especially service organizations) come to believe this, for achieving competitive advantage and long term survival in the market they should establish and develop powerful brands(as one of the key success factors) (GilaniNia, and Mousavian, 1389). A strong brand creates the value for both the customer and the organization. On the other hand Brands provide the concise and useful tools to simplify the selection process for purchasing the products or services for the customers, and in the process of data and information analysis make it easier and faster and in this way it creates value for customers. On the other hand, production processes and product designs may be simply are able to copy, but the image effectuation which remains in the minds of individuals and organizations based on several years of marketing and brand experience, are not easily replaced and cannot be replicated (Keller, 2008 ). As a result, companies based on a powerful brand, can set a higher price for their products, and establish a better trade leverage; they also could increase the contribution margin and profitability and reduce their vulnerability against competitors (Aaker and Joachimsthaler, 2000). Hence many sectors of service businesses are looking for brand development opportunities, in order to achieve greater advantage in their current brands, so this issue is been determined in this study by measuring the brand equity in the company. In this study researcher used the five dimensions as following, ideal selfconcept, fit lifestyle, quality of service, employee behavior and brand awareness for measuring brand equity in the study, and also colleagues (2011) were taken into consideration.On the other hand consumer's satisfaction is essential for long term success in the business, and it is one of the most important topics in marketing (Bourhim, 2010). Since consumer satisfaction is one of the main factors that determine the long-term success in the business, for this reason, those satisfied consumers are less sensitive to the prices, so they are less affected by the competitors, and they show more loyalty than the dissatisfied customers. When the marketing team statistics are regarded, this issue needs doubled necessity of consideration. Researchers believe that the cost of attracting new customers is usually more than the maintaining the old customers. Research has shown that the five percent reduction in the number of the customers could cause the loss of 85 percent of all corporate profits and meanwhile five percent increase in the customer retention causes25 percent to 125 percent growth in the profits of company (Salari, 1383). On the other hand in any organization - whether manufacturing or service organization - the most important factor for the preservation of the organization is its customers, so that if companies succeed in satisfying and especially getting their loyalty, they could prepare growth and long-term survival for themselves. In other words, the most important issue in the companies (especially service companies), is the customer's satisfaction and if this satisfaction continues it could create loyalty and by causing the more loyalty between clients that could gain more profits (GilaniNia and Mousavian, 1389). …

3 citations

Journal ArticleDOI
TL;DR: In this paper, the role played by workplace spirituality in organizational citizenship behavior, service quality and customer satisfaction was investigated in the context of customers and employees providing services in the banking industry.
Abstract: In today highly competitive banking industry, customer loyalty and customer satisfaction with banking services are among the important preconditions for survival and growth of banks. In this context, the relationship between customers and employees providing services is of significant importance and in general it can be said that frontline employees may attract customers and gain their satisfaction and loyalty by providing services beyond their role requirements. Present research aims to study the role played by workplace spirituality in organizational citizenship behavior, service quality and customer satisfaction. In present applied research, a survey methodology was employed and questionnaire copies were distributed to the sample derived from a statistical population comprising of all staff and customers of north Tehran branches of Saman Bank. Random stratified sampling procedure was used to obtain the appropriate sample for present study. As a result of it, 230 questionnaires (equal to the total number of employees) and 341 questionnaires (according to a sample based on Krejcie & Morgan table with an estimated statistical population of 3000) were respectively distributed to employees and customers. Structural equation modelling (SEM) and LISREL software were used to study the relationships. Research findings confirmed all hypothesized relationships between the studied concepts.

Cited by
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Journal ArticleDOI
TL;DR: An adaptive logarithmic spiral-Levy FA (AD-IFA) that strengthens the firefly algorithm's local exploitation and accelerates its convergence and consistently outperforms the standard FA and LF-FA for 29 test functions and 6 real cases of global optimization problems in terms of both computation speed and derived optimum.
Abstract: Global continuous optimization is populated by its implementation in many real-world applications. Such optimization problems are often solved by nature-inspired and meta-heuristic algorithms, including the firefly algorithm (FA), which offers fast exploration and exploitation. To further strengthen FA's search for global optimum, a Levy-flight FA (LF-FA) has been developed through sampling from a Levy distribution instead of the traditional uniform one. However, due to its poor exploitation in local areas, the LF-FA does not guarantee fast convergence. To address this problem, this paper provides an adaptive logarithmic spiral-Levy FA (AD-IFA) that strengthens the LF-FA's local exploitation and accelerates its convergence. Our AD-IFA is integrated with logarithmic-spiral guidance to its fireflies’ paths, and adaptive switching between exploration and exploitation modes during the search process. Experimental results show that the AD-IFA presented in this paper consistently outperforms the standard FA and LF-FA for 29 test functions and 6 real cases of global optimization problems in terms of both computation speed and derived optimum.

95 citations

Journal ArticleDOI
TL;DR: In this article, the authors present a comprehensive survey of privacy preserving data publishing (PPDP) techniques for both graphs and relational data, and discuss the challenges of anonymizing both graphs, and elaborate promising research directions.
Abstract: Anonymization is a practical solution for preserving user’s privacy in data publishing. Data owners such as hospitals, banks, social network (SN) service providers, and insurance companies anonymize their user’s data before publishing it to protect the privacy of users whereas anonymous data remains useful for legitimate information consumers. Many anonymization models, algorithms, frameworks, and prototypes have been proposed/developed for privacy preserving data publishing (PPDP). These models/algorithms anonymize users’ data which is mainly in the form of tables or graphs depending upon the data owners. It is of paramount importance to provide good perspectives of the whole information privacy area involving both tabular and SN data, and recent anonymization researches. In this paper, we presents a comprehensive survey about SN (i.e., graphs) and relational (i.e., tabular) data anonymization techniques used in the PPDP. We systematically categorize the existing anonymization techniques into relational and structural anonymization, and present an up to date thorough review on existing anonymization techniques and metrics used for their evaluation. Our aim is to provide deeper insights about the PPDP problem involving both graphs and tabular data, possible attacks that can be launched on the sanitized published data, different actors involved in the anonymization scenario, and major differences in amount of private information contained in graphs and relational data, respectively. We present various representative anonymization methods that have been proposed to solve privacy problems in application-specific scenarios of the SNs. Furthermore, we highlight the user’s re-identification methods used by malevolent adversaries to re-identify people uniquely from the privacy preserved published data. Additionally, we discuss the challenges of anonymizing both graphs and tabular data, and elaborate promising research directions. To the best of our knowledge, this is the first work to systematically cover recent PPDP techniques involving both SN and relational data, and it provides a solid foundation for future studies in the PPDP field.

76 citations

Journal ArticleDOI
TL;DR: In this paper, a comprehensive approach for multi-criteria decision analysis (MCDA) based on alternative methods capable of assessing different aspects of supplier selection uncertainty in terms of utility functions and criteria related to efficiency is presented.
Abstract: The focus of this paper is on selecting suppliers in the Oil and Gas (O&G) industry by developing a comprehensive approach for Multi-Criteria Decision Analysis (MCDA) based on alternative methods capable of assessing different aspects of supplier selection uncertainty in terms of utility functions and criteria related to efficiency. The O&G industry has a key role in the public sector of various countries such as Iran with its revenues being of prime importance to develop infrastructure facilities such as for healthcare, education, and transportation. This comprehensive approach walks through various stages for selecting Critical Success Factors (CSFs), ranking suppliers, and for setting partial weighting alternatives. While CSFs are selected using a traditional Delphi approach, the partial supplier rankings are defined based on Complex Proportional Assessment (COPRAS) utility functions together with criteria weights derived from Step-wise Weight Assessment Ratio Analysis (SWARA) for each CSF. As it concerns information reliability of utility and efficiency functions of both methods obtained via expert preferences or perceptions, Z-numbers are used to address the intrinsic fuzziness level inherent to each analytical stage. Iran's economy depends on revenues from oil and other related production, which means that by earning more income from this industry, most of its economic indicators such as GDP and employment rate should increase significantly, thus leading to economic growth. Various countries put plans in place related to production for increasing their social economics. One of these plans is focused on suppliers since they have a high impact on providing essential items such as equipment, HR, and transportation, so by choosing the best suppliers in all fields, costs will decrease and consequently revenue will increase. This research points out how to rank O&G industry suppliers using MCDA methods in an uncertain environment. An example based on actual data from an Iranian O&G company is provided to show the applicability of the approach proposed. Results suggest that the complexity of O&G operations on selecting suppliers can be adequately handled by information reliability techniques applied to traditional economic concepts such as utility- and efficiency-related factors, particularly in business environments characterized by a trade embargo.

33 citations

Journal ArticleDOI
TL;DR: In this paper , a Bayesian model averaging (BMA) was used to quantify the uncertainty of model parameters and inputs simultaneously, and the results indicated that BMA using multiple adaptive neuro-fuzzy interface system (ANFIS) and multi-layer perceptron (MLP) was useful for predicting tomato yield.

31 citations

Proceedings Article
01 Jan 2006
TL;DR: The generalized theory of uncertainty (GTU) as mentioned in this paper is a generalization of probability theory, which is based on the assumption that information is statistical in nature, with statistical uncertainty being a special, albeit important case.
Abstract: Uncertainty is an attribute of information. The path-breaking work of Shannon has led to a universal acceptance of the thesis that information is statistical in nature. Concomitantly, existing theories of uncertainty are based on probability theory. The generalized theory of uncertainty (GTU) departs from existing theories in essential ways. First, the thesis that information is statistical in nature is replaced by a much more general thesis that information is a generalized constraint, with statistical uncertainty being a special, albeit important case. Equating information to a generalized constraint is the fundamental thesis of GTU. Second, bivalence is abandoned throughout GTU, and the foundation of GTU is shifted from bivalent logic to fuzzy logic. As a consequence, in GTU everything is or is allowed to be a matter of degree or, equivalently, fuzzy. Concomitantly, all variables are, or are allowed to be granular, with a granule being a clump of values drawn together by a generalized constraint. And third, one of the principal objectives of GTU is achievement of NL-capability, that is, the capability to operate on information described in natural language. NL-capability has high importance because much of human knowledge, including knowledge about probabilities, is described in natural language. NL-capability is the focus of attention in the present paper. The centerpiece of GTU is the concept of a generalized constraint. The concept of a generalized constraint is motivated by the fact that most real-world constraints are elastic rather than rigid, and have a complex structure even when simple in appearance. The paper concludes with examples of computation with uncertain information described in natural language.

30 citations