Relevant bibliographies by topics / Mobile Telecom Networks

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  1. Journal articles

Academic literature on the topic 'Mobile Telecom Networks'

Author: Grafiati
Published: 6 September 2023

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Journal articles on the topic "Mobile Telecom Networks"

1

Hu, Xinxin, Haotian Chen, Hongchang Chen, Xing Li, Junjie Zhang, and Shuxin Liu. "Mining Mobile Network Fraudsters with Augmented Graph Neural Networks." Entropy 25, no. 1 (2023): 150. http://dx.doi.org/10.3390/e25010150.

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With the rapid evolution of mobile communication networks, the number of subscribers and their communication practices is increasing dramatically worldwide. However, fraudsters are also sniffing out the benefits. Detecting fraudsters from the massive volume of call detail records (CDR) in mobile communication networks has become an important yet challenging topic. Fortunately, Graph neural network (GNN) brings new possibilities for telecom fraud detection. However, the presence of the graph imbalance and GNN oversmoothing problems makes fraudster detection unsatisfactory. To address these problems, we propose a new fraud detector. First, we transform the user features with the help of a multilayer perceptron. Then, a reinforcement learning-based neighbor sampling strategy is designed to balance the number of neighbors of different classes of users. Next, we perform user feature aggregation using GNN. Finally, we innovatively treat the above augmented GNN as weak classifier and integrate multiple weak classifiers using the AdaBoost algorithm. A balanced focal loss function is also used to monitor the model training error. Extensive experiments are conducted on two open real-world telecom fraud datasets, and the results show that the proposed method is significantly effective for the graph imbalance problem and the oversmoothing problem in telecom fraud detection.
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2

Nimako, Simon Gyasi, and Joseph Mbawuni. "Examining Switching Intentions, Partial and Total Switching among Mobile Subscribers in Ghana." International Business Research 9, no. 5 (2016): 36. http://dx.doi.org/10.5539/ibr.v9n5p36.

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<p>This paper empirically explores consumer switching intentions, partial and total switching situations in the Ghana mobile telecom industry. Using data from a cross-sectional survey of 736 mobile subscribers from six global telecom networks in Ghana’s mobile telecommunication industry, the results indicate switching intentions are significantly different among customers of various mobile telecom service providers. Customers of MTN and Tigo mobile operators have stronger intentions to switch than those from the other firms. It also found that more non-porters defect and switch to other mobile networks than porters do. Consistent with the hypothesis, defectors (partial switching) are strongly associated with total switching behaviour than non-defectors. Also, in order to reduce subscriber defect or churn rate, mobile telecom operators should direct more effort and resource to promoting and educating their customers on the benefits of porting their mobile numbers to other networks. Theoretical and managerial implications are discussed. The paper contributes to the body of knowledge in the area of consumer switching behaviour in mobile telecom industry in emerging countries.</p>
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3

Daradkeh, Dr Yousef Ibrahim, Mujahed ALdhaifallah, and Dmitry Namiot. "One Model of Geo-Location Services for Telecom Operators." International Journal of Interactive Mobile Technologies (iJIM) 10, no. 2 (2016): 19. http://dx.doi.org/10.3991/ijim.v10i2.5189.

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This paper discusses location-based service for telecom providers. Most of the location-based services in the mobile networks are introduced and deployed by Internet companies. It leaves for telecom just the role of the data channel. Telecom providers should use their competitive advantages and offer own solutions. In our article, we discuss the sharing location information via geo messages. Geo messages let mobile users share location information as signatures to the standard messages (e.g., email, SMS). Rather than let some service constantly monitor (poll) the user’s location (as the most standalone services do) or share location info within any social circle (social network check-in, etc.) The Geo Messages approach lets users share location data on the peer to peer basis. Users can share own location info with any existing messaging systems. And messaging (e.g., SMS) is the traditional service for telecom.
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4

Evren, Sadi, and Atik Kulakli. "Macroeconomic ICT Facts and Mobile Telecom Operators via Social Networks and Web Pages." Journal of Economics, Business and Management 4, no. 2 (2016): 99–103. http://dx.doi.org/10.7763/joebm.2016.v4.374.

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5

Chand, Gyan, and Dr Rajeev Kumar Singh. "A Critical Study on Impact of Advertisement on Airtel Mobile Service Users with Special Reference to Bhagalpur City." GIS Business 14, no. 6 (2019): 500–509. http://dx.doi.org/10.26643/gis.v14i6.14028.

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In the 21st century, mobile has developed as basic framework to interface residents, organizations, and networks the same to new chances. However for an excessive number of networks, the guarantee of fast, affordable, and reliable telecom access remains unrealized. Mobile connectivity has been changing our lives today and contacting the correct group of spectators made simple by telecom specialist co-op and consumer loyalty which changes over into deals. In this publicizing assume imperative job in coming to the unreached as far as online administrations. In this specific circumstance, an endeavour has been had to investigate the effect of promoting on offers of Airtel mobile services.
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6

Chen, Xu. "Optimizing MPBSM Resource Allocation Based on Revenue Management: A China Mobile Sichuan Case." Mobile Information Systems 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/892705.

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The key to determining the network service level of telecom operators is resource allocation for mobile phone base station maintenance (MPBSM). Given intense market competition and higher consumer requirements for network service levels, an increasing proportion of resources have been allocated to MPBSM. Maintenance costs account for the rising fraction of direct costs, and the management of MPBSM resource allocation presents special challenges to telecom operators. China Mobile is the largest telecom operator in the world. Its subsidiary, China Mobile Sichuan, is the first in China to use revenue management in improving MPBSM resource allocation. On the basis of comprehensive revenue (including both economic revenue and social revenue), the subsidiary established a classification model of its base stations. The model scientifically classifies more than 25,000 base stations according to comprehensive revenue. China Mobile Sichuan also conducted differentiation allocation of MPBSM resources on the basis of the classification results. Furthermore, it optimized the assessment system of the telecom base stations to establish an assurance system for the use of MPBSM resources. After half-year implementation, the cell availability of both VIP base stations and total base stations significantly improved. The optimization also reduced economic losses to RMB 10.134 million, and enhanced customer satisfaction with network service by 3.2%.
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7

Aghara, Vincent NO, Ogwo E. Ogwo, and Obinna C. Ojiaku. "Analysis of Customers Acquisition Behaviour of Multiple SIM Networks Among University Lecturers in Southeast Nigeria." Business and Management Horizons 7, no. 1 (2019): 78. http://dx.doi.org/10.5296/bmh.v7i1.14690.

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As the voice-service-market of mobile telecommunication providers fast reaches its saturation amidst increasing competition, its revenue potential to telecom providers continue to decline. Therefore, understanding consumers use behavior portends important strategic consideration for customer acquisition and retention for telecom operators. This study seeks to empirically determine the factors that influence the acquisition of multiple GSM networks by university lecturers in Southeastern universities in Nigeria. Data were generated from a sample of 301 respondents. Three hypotheses were stated and tested using Analysis of variance (ANOVA). The result shows positive relationships between income, social affinity networks, and brand image and consumer acquisition of multi SIM networks. It is therefore, recommended that income, social affinity, and brand image be used as strategic marketing tools to attract customers to acquire a particular network.
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8

Liu, Jie. "Process and Application of Supply Chain Management on Telecom Operator Industry." Advanced Materials Research 630 (December 2012): 451–57. http://dx.doi.org/10.4028/www.scientific.net/amr.630.451.

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Organizations increasingly find that they must rely on effective supply chains, or networks, to compete in the global market and networked economy. This template explains and demonstrates the value, process, and application of supply chain management. Analyzed the participants which consist of m-commerce supply chain in China and how these participants create value and how information or service flows through the whole supply chain by investigating top three mobile network operators in China, China Mobile, China Unicom and China Telecom.
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9

XU, Hui-yang, Mei-na SONG, Hui CHEN, and Jun-de SONG. "Research on SOA based mobile mashup platform for telecom networks." Journal of China Universities of Posts and Telecommunications 15 (September 2008): 31–36. http://dx.doi.org/10.1016/s1005-8885(08)60150-8.

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10

Sultan, Kashif, Hazrat Ali, Adeel Ahmad, and Zhongshan Zhang. "Call Details Record Analysis: A Spatiotemporal Exploration toward Mobile Traffic Classification and Optimization." Information 10, no. 6 (2019): 192. http://dx.doi.org/10.3390/info10060192.

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The information contained within Call Details records (CDRs) of mobile networks can be used to study the operational efficacy of cellular networks and behavioural pattern of mobile subscribers. In this study, we extract actionable insights from the CDR data and show that there exists a strong spatiotemporal predictability in real network traffic patterns. This knowledge can be leveraged by the mobile operators for effective network planning such as resource management and optimization. Motivated by this, we perform the spatiotemporal analysis of CDR data publicly available from Telecom Italia. Thus, on the basis of spatiotemporal insights, we propose a framework for mobile traffic classification. Experimental results show that the proposed model based on machine learning technique is able to accurately model and classify the network traffic patterns. Furthermore, we demonstrate the application of such insights for resource optimisation.
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