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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| Other Authors: | |
| Format: | Others |
| Language: | zh-TW |
| Published: |
2018
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| Online Access: | http://ndltd.ncl.edu.tw/handle/4682ft |
| Summary: | 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.
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