An Implementation of Call-Center Data and Activities Analytics Using ELK Stack Environment
碩士 === 東海大學 === 資訊工程學系 === 106 === Cloud computing, Internet, machine learning, Internet of things and Big data has become a Big data era of technology this paper using ELK Stack deal with large data. ELK is based on Elasticsearch (E), Logstash (L), Kibana (K) three systems to handle large amounts o...
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ndltd-TW-106THU003940062019-05-16T00:08:07Z http://ndltd.ncl.edu.tw/handle/4682ft An Implementation of Call-Center Data and Activities Analytics Using ELK Stack Environment 以 ELK Stack 環境建置 Call-Center 資料 數據與活動分析 Chih-Kai Yang 楊智凱 碩士 東海大學 資訊工程學系 106 Cloud computing, Internet, machine learning, Internet of things and Big data has become a Big data era of technology this paper using ELK Stack deal with large data. ELK is based on Elasticsearch (E), Logstash (L), Kibana (K) three systems to handle large amounts of data. In each company or school and even any organization may establish a Call-Center (voice call center) environment. The Call-Center environment generated by the voice data into the ELK Stack for analysis and comparison and thus provide users with more accurate and reliable dialing behavior. Assist the future for a specific time period a specific person. The effective recommendation of the user to improve the completion of efficiency.ELK Stack system with Call-Center needs analysis of voice data. The paper experiment currently combines the voice data center age, activity information, willingness to join or not. The ratio of men and women analysis with reference to the field of data. Such as dial-up rate and dial-up time and as to be able to analyze or assist callers in raising telephone calls to enhance the enthusiasm and interest of customers. The analysis results are provided in a more effective manner at the right time System users and decision makers. Chao-Tung Yang 楊朝棟 2018 學位論文 ; thesis 80 zh-TW |
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碩士 === 東海大學 === 資訊工程學系 === 106 === Cloud computing, Internet, machine learning, Internet of things and Big data
has become a Big data era of technology this paper using ELK Stack deal with
large data. ELK is based on Elasticsearch (E), Logstash (L), Kibana (K) three
systems to handle large amounts of data. In each company or school and even
any organization may establish a Call-Center (voice call center) environment. The
Call-Center environment generated by the voice data into the ELK Stack for analysis
and comparison and thus provide users with more accurate and reliable dialing
behavior. Assist the future for a specific time period a specific person. The effective
recommendation of the user to improve the completion of efficiency.ELK
Stack system with Call-Center needs analysis of voice data. The paper experiment
currently combines the voice data center age, activity information, willingness to
join or not. The ratio of men and women analysis with reference to the field of
data. Such as dial-up rate and dial-up time and as to be able to analyze or assist
callers in raising telephone calls to enhance the enthusiasm and interest of customers.
The analysis results are provided in a more effective manner at the right
time System users and decision makers.
|
author2 |
Chao-Tung Yang |
author_facet |
Chao-Tung Yang Chih-Kai Yang 楊智凱 |
author |
Chih-Kai Yang 楊智凱 |
spellingShingle |
Chih-Kai Yang 楊智凱 An Implementation of Call-Center Data and Activities Analytics Using ELK Stack Environment |
author_sort |
Chih-Kai Yang |
title |
An Implementation of Call-Center Data and Activities Analytics Using ELK Stack Environment |
title_short |
An Implementation of Call-Center Data and Activities Analytics Using ELK Stack Environment |
title_full |
An Implementation of Call-Center Data and Activities Analytics Using ELK Stack Environment |
title_fullStr |
An Implementation of Call-Center Data and Activities Analytics Using ELK Stack Environment |
title_full_unstemmed |
An Implementation of Call-Center Data and Activities Analytics Using ELK Stack Environment |
title_sort |
implementation of call-center data and activities analytics using elk stack environment |
publishDate |
2018 |
url |
http://ndltd.ncl.edu.tw/handle/4682ft |
work_keys_str_mv |
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