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Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
Issue Info: 
  • Year: 

    2019
  • Volume: 

    8
  • Issue: 

    2
  • Pages: 

    1-16
Measures: 
  • Citations: 

    0
  • Views: 

    598
  • Downloads: 

    0
Abstract: 

Using online reviews is one of the main factors in customers’ decision making for buying a product or using a service. These reviews are valuable sources of information which can be used for detecting public opinion about products or services. Although online reviews are useful, trusting them blindly is dangerous for both costumers and sellers as they may be manipulated by spammers to earn profit; such reviews are called spam reviews. The current study addresses Persian reviews about cell-phone extracted from Digikala. com and investigates spam type 1 and type 2 which are fake reviews and reviews describing brands’ names only, respectively. Features used in this study, due to their efficiency, are review-based and metadata features. These features and their combinations in detecting Persian spam reviews, also their effect on the accuracy of classifier are assessed. Spam classification is performed using decision tree, support vector machines, and naï ve Bayes classifiers and their accuracy are compared using different features’ combinations. The highest accuracy is obtained using the decision tree classifier which achieves 0. 778 in terms of F-measure. In ranking features, again the decision tree outperforms the other two classifiers by achieving 0. 824 F-measure by combining the positive feedback, overall score, and review polarity features.

Yearly Impact: مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

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Issue Info: 
  • Year: 

    2019
  • Volume: 

    8
  • Issue: 

    2
  • Pages: 

    17-26
Measures: 
  • Citations: 

    0
  • Views: 

    438
  • Downloads: 

    0
Abstract: 

Cloud computing is considered as a new method of computations where resources can be scaled and provides services in virtualized format using the Internet. In some cases, the user’ s need is in a way that the underlying service cannot meet user’ s need individually and it is needed to combine services in order to meet the requirements. The previously presented methods had some problems such as not checking the cost, energy consumption, and not providing a framework for using the lowest number of clouds to respond to user requests. Therefore, the proposed method in this paper combines an ant colony algorithm with a based cloud algorithm (ACOBC). In this method, first, the cloud compositions that can respond to user requests are arranged in ascending order based on the number of clouds in the cloud composition, then the ant colony algorithm selects the appropriate services from each category, respectively. The obtained results have shown that the proposed method can act better energy consumption and cost.

Yearly Impact: مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

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Author(s): 

Dinparast Saber | Hashemi Golpaygani Seyyed Alireza

Issue Info: 
  • Year: 

    2019
  • Volume: 

    8
  • Issue: 

    2
  • Pages: 

    27-43
Measures: 
  • Citations: 

    0
  • Views: 

    304
  • Downloads: 

    0
Abstract: 

Build-to-order supply chains are categorized as agile supply chains, therefore reshaping their physical structure is inevitable. The reshape affects chains material flow pattern, therefore revising the chains information flow pattern becomes a necessity. The revision should create the most coordinated information flow pattern with the new physical structure. Hence, we have tried to study and survey the way material flows in supply chain affects its information flow and vice versa. We have thought up a model in which mathematical modeling establishes coordinated information and material flow patterns. To achieve this, the parameters which build the two flow patterns were studied and considered. Each parameter’ s effects on others has been studied and relations were extracted. Using the capabilities of mathematical modeling the studied system converted to a Mixed Integer Non-Linear Programming (MINLP) model in which, some parameters as inputs give away the most coordinated information and material flow with chains physical structure considering minimum cost as objective.

Yearly Impact: مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

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Issue Info: 
  • Year: 

    2019
  • Volume: 

    8
  • Issue: 

    2
  • Pages: 

    44-54
Measures: 
  • Citations: 

    0
  • Views: 

    531
  • Downloads: 

    0
Abstract: 

Placement of virtual machines on physical machines in cloud computing infrastructure is an important issue. Our approach for placement of virtual machines includes a mapping process of this machines on physical machines in cloud datacenters. Optimal placement results in lower power consumption, optimal usage of resources, traffic reduce in datacenters, decrease in costs and also increase in functionality of datacenters in cloud datacenters. In this paper we propose a discrete gravitational search algorithm and chaotic function for placement of virtual machines on physical machines in cloud datacenters. Our primary goal for proposing the approach is minimizing resource wastage, power consumption and network links. At the end of this paper we also compare our results with some other metaheuristic algorithms. Our results show that this approach is more effective than previous algorithms.

Yearly Impact: مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

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Author(s): 

raji fatemeh

Issue Info: 
  • Year: 

    2019
  • Volume: 

    8
  • Issue: 

    2
  • Pages: 

    55-75
Measures: 
  • Citations: 

    0
  • Views: 

    274
  • Downloads: 

    0
Abstract: 

Cloud computing technology has attracted the attention of researchers in recent years. Providing user security in terms of anonymity is one of the most important challenges in the context of cloud computing so that the user identity is concealed to others, including the cloud computing provider. Although there are researches for providing anonymity in the network communications, there are limited works for providing the anonymity feature in the cloud computing context. In this paper, we propose an anonymity approach to provide the anonymity of cloud users against the cloud provider and make the user to be resistant against traffic analysis attacks. In this way, all the communication messages between users and the provider have been passed through a set of intermediate hosts in encrypted forms. Therefore, not only the users request messages but also the provider response messages are resistant against traffic analysis attackers. Moreover, the integrity and confidentiality of the messages communicated between the user and the provider are prepared and the user is able to have high flexibility in reaching his/her desired anonymity. The accurate anonymity and efficiency analysis of the proposed approach shows that this method is resistant against known traffic analysis attacks without relying on heavy assumptions.

Yearly Impact: مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

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Issue Info: 
  • Year: 

    2019
  • Volume: 

    8
  • Issue: 

    2
  • Pages: 

    76-88
Measures: 
  • Citations: 

    0
  • Views: 

    380
  • Downloads: 

    0
Abstract: 

The relative position and orientation parameters between two cameras in a stereo pair are included within the Essential matrix, E. The decomposition of this matrix into a rotation matrix, R, and a skew-symmetric matrix, S, is an efficient tool for retrieving the relative position and orientation of the cameras. In this paper, a new method is proposed to recover these parameters using the singular value decomposition (SVD) of the Essential matrix. First, using the SVD properties, the existing formulas in the decomposition of the Essential matrix into a rotation matrix and a skew-symmetric matrix are directly proved. Then, based on these results, a new method in the decomposition of the Essential matrix using SVD will be presented. The Essential matrix decomposition in this method is accomplished by extracting the base vector of the left null space of the Essential matrix and then followed by SVD decomposition of the skew-symmetric matrix corresponding to this base vector. In this method, the initial mapping of the Essential matrix, recovered from the erroneous coordinates of the corresponding image points in two images, into the space of Essential matrices does not require. The numerical analysis shows that the results of the new presented method are correct and identical with the results of the existing formulas.

Yearly Impact: مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

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Issue Info: 
  • Year: 

    2019
  • Volume: 

    8
  • Issue: 

    2
  • Pages: 

    89-101
Measures: 
  • Citations: 

    0
  • Views: 

    325
  • Downloads: 

    0
Abstract: 

Sentiment classification of opinions is a field of Natural Language Processing which has been considered in recent years by researchers due to popularity of Internet stores and the possibility of expressing opinions about sold goods or services. To train classifier models, we need labeled datasets, but as there are not rich labeled samples and as labeling is a difficult and time-consuming process, we must employ labeled samples of other domains. In this article, a new method for binary classification of opinions is proposed based on multi-domain transfer learning. The proposed method tries to adapt different domains by using Structural Correspondence Learning; and based on repetitive procedure of the boosting algorithm, a weight is assigned to classified samples of different domains and the class of each opinion is specified by merging these classifiers. Weighting the dataset samples to boost the process of classification based on the Adaboost algorithm and combining it with the Structural Corresponding Learning is the most important innovation of the current research. The Amazon dataset of four different domains, each one containing 1000 positive and 1000 negative opinions is used for training the proposed model. Accuracy measures of %89. 64, %93. 97, %92. 39 and %90. 17 are obtained for Electronics, DVD, Books and Kitchen domains, respectively. It illustrates that the proposed method is very effective compared with the similar methods.

Yearly Impact: مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

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