A Study on Hotel Customer Reputation Analysis based on Big Data

Kong, Hyo-Soon; Song, Eun-Jee

doi:10.9728/dcs.2014.15.2.219

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2016

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“…The findings are expected to help the travel agency analyze the extracted risk factors and take corrective measures. It is also expected that the proposed system can be applied to other s of the service industry such as hotels and hospitals [9][10].…”

Section: Discussionmentioning

confidence: 99%

A Study on Customer Feedback by VOC Big Data Analysis of for Travel Agencies

Song

2016

IJUNESST

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Section: Discussionmentioning

confidence: 99%

A Study on Customer Feedback by VOC Big Data Analysis of for Travel Agencies

Song

2016

IJUNESST

Self Cite

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“…Currently, service providers are looking to leverage the new generation of "Big Data" [9][10] analytics tools and techniques to exploit the untapped reservoirs of data that exist within their network and IT systems. The fine-grained data that can be collected from network probes, intelligent sensors and other data sources are the fuel that powers big data analytics and provides new insights into ways to improve customer experience, optimize networks, drive greater operational efficiency, and enable broader service offerings.…”

Section: Introductionmentioning

confidence: 99%

A Dynamical Load Balancing Method for Data Streaming and User Request in WebRTC Environment

Van¹,

Park²,

Jang³

et al. 2016

Journal of Digital Contents Society

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WebRTC has quickly grown to be the world's advanced real-time communication in several platforms such as web and mobile. In spite of the advantage, the current technology in WebRTC does not handle a big-streaming efficiently between peers and a large amount request of users on the Signaling server. Therefore, in this paper, we put our work to handle the problem by delivering the flow of data with dynamical load balancing algorithms. We analyze the request source users and direct those streaming requests to a load balancing component. More specifically, the component determines an amount of the requested resource and available resource on the response server, then it delivers streaming data to the requesting user parallel or alternately. To show how the method works, we firstly demonstrate the load-balancing algorithm by using a network simulation tool OPNET, then, we seek to implement the method into an Ubuntu server. In addition, we compare the result of our work and the original implementation of WebRTC, it shows that the method performs efficiently and dynamically than the origin.

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A Study on Hotel Customer Reputation Analysis based on Big Data

Cited by 2 publications

References 1 publication

A Study on Customer Feedback by VOC Big Data Analysis of for Travel Agencies

A Study on Customer Feedback by VOC Big Data Analysis of for Travel Agencies

A Dynamical Load Balancing Method for Data Streaming and User Request in WebRTC Environment

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